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meta_all.arff
null
{0: [0 - openml_task_id (numeric)], 1: [1 - meta_REPTreeDepth2ErrRate (numeric)], 2: [2 - meta_J48.00001.ErrRate (numeric)], 3: [3 - meta_NBErrRate (numeric)], 4: [4 - meta_MeanMutualInformation (numeric)], 5: [5 - meta_NBAUC (numeric)], 6: [6 - meta_DecisionStumpKappa (numeric)], 7: [7 - meta_HoeffdingDDM.warni...
{'MajorityClassSize': 42.0, 'MaxNominalAttDistinctValues': 6.0, 'MinorityClassSize': 2.0, 'NumberOfClasses': 6.0, 'NumberOfFeatures': 63.0, 'NumberOfInstances': 71.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 62.0, 'NumberOfSymbolicFeatures': 1.0, 'cos...
meta_all.arff
[ "openml_task_id", "meta_REPTreeDepth2ErrRate", "meta_J48.00001.ErrRate", "meta_NBErrRate", "meta_MeanMutualInformation", "meta_NBAUC", "meta_DecisionStumpKappa", "meta_HoeffdingDDM.warnings", "meta_NoiseToSignalRatio", "meta_RandomTreeDepth3AUC_K=0", "meta_PercentageOfNumericAtts", "meta_Equiv...
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1,458
1,957
predictive_accuracy
accuracy_score
mfeat-karhunen
**Author**: Robert P.W. Duin, Department of Applied Physics, Delft University of Technology **Source**: [UCI](https://archive.ics.uci.edu/ml/datasets/Multiple+Features) - 1998 **Please cite**: [UCI](https://archive.ics.uci.edu/ml/citation_policy.html) **Multiple Features Dataset: Karhunen** One of a set of 6 ...
{0: [0 - att1 (numeric)], 1: [1 - att2 (numeric)], 2: [2 - att3 (numeric)], 3: [3 - att4 (numeric)], 4: [4 - att5 (numeric)], 5: [5 - att6 (numeric)], 6: [6 - att7 (numeric)], 7: [7 - att8 (numeric)], 8: [8 - att9 (numeric)], 9: [9 - att10 (numeric)], 10: [10 - att11 (numeric)], 11: [11 - att12 (numeric)], ...
{'MajorityClassSize': 200.0, 'MaxNominalAttDistinctValues': 10.0, 'MinorityClassSize': 200.0, 'NumberOfClasses': 10.0, 'NumberOfFeatures': 65.0, 'NumberOfInstances': 2000.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 64.0, 'NumberOfSymbolicFeatures': 1.0...
mfeat-karhunen
[ "att1", "att2", "att3", "att4", "att5", "att6", "att7", "att8", "att9", "att10", "att11", "att12", "att13", "att14", "att15", "att16", "att17", "att18", "att19", "att20", "att21", "att22", "att23", "att24", "att25", "att26", "att27", "att28", "att29", "att30...
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1,459
2,124
predictive_accuracy
accuracy_score
braziltourism
**Author**: **Source**: Unknown - **Please cite**: analcatdata A collection of data sets used in the book "Analyzing Categorical Data," by Jeffrey S. Simonoff, Springer-Verlag, New York, 2003. The submission consists of a zip file containing two versions of each of 84 data s...
{0: [0 - Age (numeric)], 1: [1 - Sex (nominal)], 2: [2 - Income (numeric)], 3: [3 - Travel_cost (numeric)], 4: [4 - Access_road (nominal)], 5: [5 - Active (nominal)], 6: [6 - Passive (nominal)], 7: [7 - Logged_income (numeric)], 8: [8 - Trips (nominal)]}
{'MajorityClassSize': 318.0, 'MaxNominalAttDistinctValues': 7.0, 'MinorityClassSize': 1.0, 'NumberOfClasses': 7.0, 'NumberOfFeatures': 9.0, 'NumberOfInstances': 412.0, 'NumberOfInstancesWithMissingValues': 49.0, 'NumberOfMissingValues': 96.0, 'NumberOfNumericFeatures': 4.0, 'NumberOfSymbolicFeatures': 5.0, 'c...
braziltourism
[ "Age", "Sex", "Income", "Travel_cost", "Access_road", "Active", "Passive", "Logged_income" ]
[ false, true, false, false, true, true, true, false ]
1,460
2,352
predictive_accuracy
accuracy_score
meta_all.arff
null
{0: [0 - openml_task_id (numeric)], 1: [1 - meta_REPTreeDepth2ErrRate (numeric)], 2: [2 - meta_J48.00001.ErrRate (numeric)], 3: [3 - meta_NBErrRate (numeric)], 4: [4 - meta_MeanMutualInformation (numeric)], 5: [5 - meta_NBAUC (numeric)], 6: [6 - meta_DecisionStumpKappa (numeric)], 7: [7 - meta_HoeffdingDDM.warni...
{'MajorityClassSize': 42.0, 'MaxNominalAttDistinctValues': 6.0, 'MinorityClassSize': 2.0, 'NumberOfClasses': 6.0, 'NumberOfFeatures': 63.0, 'NumberOfInstances': 71.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 62.0, 'NumberOfSymbolicFeatures': 1.0, 'cos...
meta_all.arff
[ "openml_task_id", "meta_REPTreeDepth2ErrRate", "meta_J48.00001.ErrRate", "meta_NBErrRate", "meta_MeanMutualInformation", "meta_NBAUC", "meta_DecisionStumpKappa", "meta_HoeffdingDDM.warnings", "meta_NoiseToSignalRatio", "meta_RandomTreeDepth3AUC_K=0", "meta_PercentageOfNumericAtts", "meta_Equiv...
[ false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, f...
1,461
2,121
predictive_accuracy
accuracy_score
abalone
**Author**: **Source**: Unknown - **Please cite**: 1. Title of Database: Abalone data 2. Sources: (a) Original owners of database: Marine Resources Division Marine Research Laboratories - Taroona Department of Primary Industry and Fisheries, Tasmania GPO Box 619F, Hobart, Tasmania 7001, Austr...
{0: [0 - Sex (nominal)], 1: [1 - Length (numeric)], 2: [2 - Diameter (numeric)], 3: [3 - Height (numeric)], 4: [4 - Whole_weight (numeric)], 5: [5 - Shucked_weight (numeric)], 6: [6 - Viscera_weight (numeric)], 7: [7 - Shell_weight (numeric)], 8: [8 - Class_number_of_rings (nominal)]}
{'MajorityClassSize': 689.0, 'MaxNominalAttDistinctValues': 28.0, 'MinorityClassSize': 1.0, 'NumberOfClasses': 28.0, 'NumberOfFeatures': 9.0, 'NumberOfInstances': 4177.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 7.0, 'NumberOfSymbolicFeatures': 2.0, '...
abalone
[ "Sex", "Length", "Diameter", "Height", "Whole_weight", "Shucked_weight", "Viscera_weight", "Shell_weight" ]
[ true, false, false, false, false, false, false, false ]
1,462
2,274
predictive_accuracy
accuracy_score
meta_ensembles.arff
null
{0: [0 - openml_task_id (numeric)], 1: [1 - meta_REPTreeDepth2ErrRate (numeric)], 2: [2 - meta_J48.00001.ErrRate (numeric)], 3: [3 - meta_NBErrRate (numeric)], 4: [4 - meta_MeanMutualInformation (numeric)], 5: [5 - meta_NBAUC (numeric)], 6: [6 - meta_DecisionStumpKappa (numeric)], 7: [7 - meta_HoeffdingDDM.warni...
{'MajorityClassSize': 45.0, 'MaxNominalAttDistinctValues': 4.0, 'MinorityClassSize': 5.0, 'NumberOfClasses': 4.0, 'NumberOfFeatures': 63.0, 'NumberOfInstances': 74.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 62.0, 'NumberOfSymbolicFeatures': 1.0, 'cos...
meta_ensembles.arff
[ "openml_task_id", "meta_REPTreeDepth2ErrRate", "meta_J48.00001.ErrRate", "meta_NBErrRate", "meta_MeanMutualInformation", "meta_NBAUC", "meta_DecisionStumpKappa", "meta_HoeffdingDDM.warnings", "meta_NoiseToSignalRatio", "meta_RandomTreeDepth3AUC_K=0", "meta_PercentageOfNumericAtts", "meta_Equiv...
[ false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, f...
1,463
2,119
predictive_accuracy
accuracy_score
yeast
**Author**: **Source**: Unknown - **Please cite**:
{0: [0 - mcg (numeric)], 1: [1 - gvh (numeric)], 2: [2 - alm (numeric)], 3: [3 - mit (numeric)], 4: [4 - erl (numeric)], 5: [5 - pox (numeric)], 6: [6 - vac (numeric)], 7: [7 - nuc (numeric)], 8: [8 - class_protein_localization (nominal)]}
{'MajorityClassSize': 463.0, 'MaxNominalAttDistinctValues': 10.0, 'MinorityClassSize': 5.0, 'NumberOfClasses': 10.0, 'NumberOfFeatures': 9.0, 'NumberOfInstances': 1484.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 8.0, 'NumberOfSymbolicFeatures': 1.0, '...
yeast
[ "mcg", "gvh", "alm", "mit", "erl", "pox", "vac", "nuc" ]
[ false, false, false, false, false, false, false, false ]
1,464
2,075
predictive_accuracy
accuracy_score
abalone
**Author**: **Source**: Unknown - **Please cite**: 1. Title of Database: Abalone data 2. Sources: (a) Original owners of database: Marine Resources Division Marine Research Laboratories - Taroona Department of Primary Industry and Fisheries, Tasmania GPO Box 619F, Hobart, Tasmania 7001, Austr...
{0: [0 - Sex (nominal)], 1: [1 - Length (numeric)], 2: [2 - Diameter (numeric)], 3: [3 - Height (numeric)], 4: [4 - Whole_weight (numeric)], 5: [5 - Shucked_weight (numeric)], 6: [6 - Viscera_weight (numeric)], 7: [7 - Shell_weight (numeric)], 8: [8 - Class_number_of_rings (nominal)]}
{'MajorityClassSize': 689.0, 'MaxNominalAttDistinctValues': 28.0, 'MinorityClassSize': 1.0, 'NumberOfClasses': 28.0, 'NumberOfFeatures': 9.0, 'NumberOfInstances': 4177.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 7.0, 'NumberOfSymbolicFeatures': 2.0, '...
abalone
[ "Sex", "Length", "Diameter", "Height", "Whole_weight", "Shucked_weight", "Viscera_weight", "Shell_weight" ]
[ true, false, false, false, false, false, false, false ]
1,465
2,273
predictive_accuracy
accuracy_score
meta_batchincremental.arff
null
{0: [0 - openml_task_id (numeric)], 1: [1 - meta_REPTreeDepth2ErrRate (numeric)], 2: [2 - meta_J48.00001.ErrRate (numeric)], 3: [3 - meta_NBErrRate (numeric)], 4: [4 - meta_MeanMutualInformation (numeric)], 5: [5 - meta_NBAUC (numeric)], 6: [6 - meta_DecisionStumpKappa (numeric)], 7: [7 - meta_HoeffdingDDM.warni...
{'MajorityClassSize': 50.0, 'MaxNominalAttDistinctValues': 4.0, 'MinorityClassSize': 3.0, 'NumberOfClasses': 4.0, 'NumberOfFeatures': 63.0, 'NumberOfInstances': 74.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 62.0, 'NumberOfSymbolicFeatures': 1.0, 'cos...
meta_batchincremental.arff
[ "openml_task_id", "meta_REPTreeDepth2ErrRate", "meta_J48.00001.ErrRate", "meta_NBErrRate", "meta_MeanMutualInformation", "meta_NBAUC", "meta_DecisionStumpKappa", "meta_HoeffdingDDM.warnings", "meta_NoiseToSignalRatio", "meta_RandomTreeDepth3AUC_K=0", "meta_PercentageOfNumericAtts", "meta_Equiv...
[ false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, f...
1,466
2,123
predictive_accuracy
accuracy_score
baseball
Database of baseball players and play statistics, including 'Games_played', 'At_bats', 'Runs', 'Hits', 'Doubles', 'Triples', 'Home_runs', 'RBIs', 'Walks', 'Strikeouts', 'Batting_average', 'On_base_pct', 'Slugging_pct' and 'Fielding_ave' Notes: * Quotes, Single-Quotes and Backslashes were removed, Blanks replaced wi...
{0: [0 - Player (nominal)], 1: [1 - Number_seasons (numeric)], 2: [2 - Games_played (numeric)], 3: [3 - At_bats (numeric)], 4: [4 - Runs (numeric)], 5: [5 - Hits (numeric)], 6: [6 - Doubles (numeric)], 7: [7 - Triples (numeric)], 8: [8 - Home_runs (numeric)], 9: [9 - RBIs (numeric)], 10: [10 - Walks (numeric)...
{'MajorityClassSize': 1215.0, 'MaxNominalAttDistinctValues': 7.0, 'MinorityClassSize': 57.0, 'NumberOfClasses': 3.0, 'NumberOfFeatures': 17.0, 'NumberOfInstances': 1340.0, 'NumberOfInstancesWithMissingValues': 20.0, 'NumberOfMissingValues': 20.0, 'NumberOfNumericFeatures': 15.0, 'NumberOfSymbolicFeatures': 2.0...
baseball
[ "Number_seasons", "Games_played", "At_bats", "Runs", "Hits", "Doubles", "Triples", "Home_runs", "RBIs", "Walks", "Strikeouts", "Batting_average", "On_base_pct", "Slugging_pct", "Fielding_ave", "Position" ]
[ false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, true ]
1,467
1,776
predictive_accuracy
accuracy_score
mfeat-factors
**Author**: Robert P.W. Duin, Department of Applied Physics, Delft University of Technology **Source**: [UCI](https://archive.ics.uci.edu/ml/datasets/Multiple+Features) - 1998 **Please cite**: [UCI](https://archive.ics.uci.edu/ml/citation_policy.html) **Multiple Features Dataset: Factors** One of a set of 6 d...
{0: [0 - att1 (numeric)], 1: [1 - att2 (numeric)], 2: [2 - att3 (numeric)], 3: [3 - att4 (numeric)], 4: [4 - att5 (numeric)], 5: [5 - att6 (numeric)], 6: [6 - att7 (numeric)], 7: [7 - att8 (numeric)], 8: [8 - att9 (numeric)], 9: [9 - att10 (numeric)], 10: [10 - att11 (numeric)], 11: [11 - att12 (numeric)], ...
{'MajorityClassSize': 200.0, 'MaxNominalAttDistinctValues': 10.0, 'MinorityClassSize': 200.0, 'NumberOfClasses': 10.0, 'NumberOfFeatures': 217.0, 'NumberOfInstances': 2000.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 216.0, 'NumberOfSymbolicFeatures': 1...
mfeat-factors
[ "att1", "att2", "att3", "att4", "att5", "att6", "att7", "att8", "att9", "att10", "att11", "att12", "att13", "att14", "att15", "att16", "att17", "att18", "att19", "att20", "att21", "att22", "att23", "att24", "att25", "att26", "att27", "att28", "att29", "att30...
[ false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, f...
1,468
2,275
predictive_accuracy
accuracy_score
meta_instanceincremental.arff
null
{0: [0 - openml_task_id (numeric)], 1: [1 - meta_REPTreeDepth2ErrRate (numeric)], 2: [2 - meta_J48.00001.ErrRate (numeric)], 3: [3 - meta_NBErrRate (numeric)], 4: [4 - meta_MeanMutualInformation (numeric)], 5: [5 - meta_NBAUC (numeric)], 6: [6 - meta_DecisionStumpKappa (numeric)], 7: [7 - meta_HoeffdingDDM.warni...
{'MajorityClassSize': 54.0, 'MaxNominalAttDistinctValues': 4.0, 'MinorityClassSize': 3.0, 'NumberOfClasses': 4.0, 'NumberOfFeatures': 63.0, 'NumberOfInstances': 74.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 62.0, 'NumberOfSymbolicFeatures': 1.0, 'cos...
meta_instanceincremental.arff
[ "openml_task_id", "meta_REPTreeDepth2ErrRate", "meta_J48.00001.ErrRate", "meta_NBErrRate", "meta_MeanMutualInformation", "meta_NBAUC", "meta_DecisionStumpKappa", "meta_HoeffdingDDM.warnings", "meta_NoiseToSignalRatio", "meta_RandomTreeDepth3AUC_K=0", "meta_PercentageOfNumericAtts", "meta_Equiv...
[ false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, f...
1,469
2,382
predictive_accuracy
accuracy_score
wine
**Author**: **Source**: Unknown - **Please cite**: 1. Title of Database: Wine recognition data Updated Sept 21, 1998 by C.Blake : Added attribute information 2. Sources: (a) Forina, M. et al, PARVUS - An Extendible Package for Data Exploration, Classification and Correlation. Institute of Pha...
{0: [0 - class (nominal)], 1: [1 - Alcohol (numeric)], 2: [2 - Malic_acid (numeric)], 3: [3 - Ash (numeric)], 4: [4 - Alcalinity_of_ash (numeric)], 5: [5 - Magnesium (numeric)], 6: [6 - Total_phenols (numeric)], 7: [7 - Flavanoids (numeric)], 8: [8 - Nonflavanoid_phenols (numeric)], 9: [9 - Proanthocyanins (nu...
{'MajorityClassSize': 71.0, 'MaxNominalAttDistinctValues': 3.0, 'MinorityClassSize': 48.0, 'NumberOfClasses': 3.0, 'NumberOfFeatures': 14.0, 'NumberOfInstances': 178.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 13.0, 'NumberOfSymbolicFeatures': 1.0, 'c...
wine
[ "Alcohol", "Malic_acid", "Ash", "Alcalinity_of_ash", "Magnesium", "Total_phenols", "Flavanoids", "Nonflavanoid_phenols", "Proanthocyanins", "Color_intensity", "Hue", "OD280%2FOD315_of_diluted_wines", "Proline" ]
[ false, false, false, false, false, false, false, false, false, false, false, false, false ]
1,470
2,353
predictive_accuracy
accuracy_score
meta_batchincremental.arff
null
{0: [0 - openml_task_id (numeric)], 1: [1 - meta_REPTreeDepth2ErrRate (numeric)], 2: [2 - meta_J48.00001.ErrRate (numeric)], 3: [3 - meta_NBErrRate (numeric)], 4: [4 - meta_MeanMutualInformation (numeric)], 5: [5 - meta_NBAUC (numeric)], 6: [6 - meta_DecisionStumpKappa (numeric)], 7: [7 - meta_HoeffdingDDM.warni...
{'MajorityClassSize': 50.0, 'MaxNominalAttDistinctValues': 4.0, 'MinorityClassSize': 3.0, 'NumberOfClasses': 4.0, 'NumberOfFeatures': 63.0, 'NumberOfInstances': 74.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 62.0, 'NumberOfSymbolicFeatures': 1.0, 'cos...
meta_batchincremental.arff
[ "openml_task_id", "meta_REPTreeDepth2ErrRate", "meta_J48.00001.ErrRate", "meta_NBErrRate", "meta_MeanMutualInformation", "meta_NBAUC", "meta_DecisionStumpKappa", "meta_HoeffdingDDM.warnings", "meta_NoiseToSignalRatio", "meta_RandomTreeDepth3AUC_K=0", "meta_PercentageOfNumericAtts", "meta_Equiv...
[ false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, f...
1,471
2,355
predictive_accuracy
accuracy_score
meta_instanceincremental.arff
null
{0: [0 - openml_task_id (numeric)], 1: [1 - meta_REPTreeDepth2ErrRate (numeric)], 2: [2 - meta_J48.00001.ErrRate (numeric)], 3: [3 - meta_NBErrRate (numeric)], 4: [4 - meta_MeanMutualInformation (numeric)], 5: [5 - meta_NBAUC (numeric)], 6: [6 - meta_DecisionStumpKappa (numeric)], 7: [7 - meta_HoeffdingDDM.warni...
{'MajorityClassSize': 54.0, 'MaxNominalAttDistinctValues': 4.0, 'MinorityClassSize': 3.0, 'NumberOfClasses': 4.0, 'NumberOfFeatures': 63.0, 'NumberOfInstances': 74.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 62.0, 'NumberOfSymbolicFeatures': 1.0, 'cos...
meta_instanceincremental.arff
[ "openml_task_id", "meta_REPTreeDepth2ErrRate", "meta_J48.00001.ErrRate", "meta_NBErrRate", "meta_MeanMutualInformation", "meta_NBAUC", "meta_DecisionStumpKappa", "meta_HoeffdingDDM.warnings", "meta_NoiseToSignalRatio", "meta_RandomTreeDepth3AUC_K=0", "meta_PercentageOfNumericAtts", "meta_Equiv...
[ false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, f...
1,472
361,287
root_mean_squared_error
root_mean_squared_error
topo_2_1
Dataset used in the tabular data benchmark https://github.com/LeoGrin/tabular-benchmark, transformed in the same way. This dataset belongs to the "regression on both numerical and categorical features" benchmark. Original link: https://openml.org/d/422 Original description: **Author**: **Source**: Unknow...
{0: [0 - oz1 (numeric)], 1: [1 - oz2 (numeric)], 2: [2 - oz3 (numeric)], 3: [3 - oz4 (numeric)], 4: [4 - oz5 (numeric)], 5: [5 - oz6 (numeric)], 6: [6 - oz7 (numeric)], 7: [7 - oz8 (numeric)], 8: [8 - oz9 (numeric)], 9: [9 - oz10 (numeric)], 10: [10 - oz11 (numeric)], 11: [11 - oz12 (numeric)], 12: [12 - oz...
{'MajorityClassSize': nan, 'MaxNominalAttDistinctValues': nan, 'MinorityClassSize': nan, 'NumberOfClasses': 0.0, 'NumberOfFeatures': 256.0, 'NumberOfInstances': 8885.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 253.0, 'NumberOfSymbolicFeatures': 3.0, '...
topo_2_1
[ "oz1", "oz2", "oz3", "oz4", "oz5", "oz6", "oz7", "oz8", "oz9", "oz10", "oz11", "oz12", "oz13", "oz14", "oz15", "oz16", "oz17", "oz18", "oz19", "oz20", "oz21", "oz22", "oz23", "oz24", "oz25", "oz26", "oz27", "oz28", "oz29", "oz30", "oz31", "oz32", "oz33...
[ false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, f...
1,473
2,922
predictive_accuracy
accuracy_score
lung-cancer
**Author**: **Source**: Unknown - **Please cite**: 1. Title: Lung Cancer Data 2. Source Information: - Data was published in : Hong, Z.Q. and Yang, J.Y. "Optimal Discriminant Plane for a Small Number of Samples and Design Method of Classifier on the Plane", Pattern Recognition, Vol. 24, No. ...
{0: [0 - class (nominal)], 1: [1 - attribute2 (nominal)], 2: [2 - attribute3 (nominal)], 3: [3 - attribute4 (nominal)], 4: [4 - attribute5 (nominal)], 5: [5 - attribute6 (nominal)], 6: [6 - attribute7 (nominal)], 7: [7 - attribute8 (nominal)], 8: [8 - attribute9 (nominal)], 9: [9 - attribute10 (nominal)], 10:...
{'MajorityClassSize': 13.0, 'MaxNominalAttDistinctValues': 4.0, 'MinorityClassSize': 9.0, 'NumberOfClasses': 3.0, 'NumberOfFeatures': 57.0, 'NumberOfInstances': 32.0, 'NumberOfInstancesWithMissingValues': 5.0, 'NumberOfMissingValues': 5.0, 'NumberOfNumericFeatures': 0.0, 'NumberOfSymbolicFeatures': 57.0, 'cos...
lung-cancer
[ "class", "attribute2", "attribute3", "attribute4", "attribute5", "attribute6", "attribute7", "attribute8", "attribute9", "attribute10", "attribute11", "attribute12", "attribute13", "attribute14", "attribute15", "attribute16", "attribute17", "attribute18", "attribute19", "attrib...
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1,474
2,931
predictive_accuracy
accuracy_score
shuttle-landing-control
# Space Shuttle Autolanding Domain NASA: Mr. Roger Burke's autolander design team ##### Past Usage: (several, it appears) Example: Michie,D. (1988). The Fifth Generation's Unbridged Gap. In Rolf Herken (Ed.) The Universal Turing Machine: A Half-Century Survey, 466-489, Oxford Uni...
{0: [0 - Class (nominal)], 1: [1 - STABILITY (nominal)], 2: [2 - ERROR (nominal)], 3: [3 - SIGN (nominal)], 4: [4 - WIND (nominal)], 5: [5 - MAGNITUDE (nominal)], 6: [6 - VISIBILITY (nominal)]}
{'MajorityClassSize': 9.0, 'MaxNominalAttDistinctValues': 4.0, 'MinorityClassSize': 6.0, 'NumberOfClasses': 2.0, 'NumberOfFeatures': 7.0, 'NumberOfInstances': 15.0, 'NumberOfInstancesWithMissingValues': 9.0, 'NumberOfMissingValues': 26.0, 'NumberOfNumericFeatures': 0.0, 'NumberOfSymbolicFeatures': 7.0, 'cost_...
shuttle-landing-control
[ "Class", "STABILITY", "ERROR", "SIGN", "WIND", "MAGNITUDE" ]
[ true, true, true, true, true, true ]
1,475
2,354
predictive_accuracy
accuracy_score
meta_ensembles.arff
null
{0: [0 - openml_task_id (numeric)], 1: [1 - meta_REPTreeDepth2ErrRate (numeric)], 2: [2 - meta_J48.00001.ErrRate (numeric)], 3: [3 - meta_NBErrRate (numeric)], 4: [4 - meta_MeanMutualInformation (numeric)], 5: [5 - meta_NBAUC (numeric)], 6: [6 - meta_DecisionStumpKappa (numeric)], 7: [7 - meta_HoeffdingDDM.warni...
{'MajorityClassSize': 45.0, 'MaxNominalAttDistinctValues': 4.0, 'MinorityClassSize': 5.0, 'NumberOfClasses': 4.0, 'NumberOfFeatures': 63.0, 'NumberOfInstances': 74.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 62.0, 'NumberOfSymbolicFeatures': 1.0, 'cos...
meta_ensembles.arff
[ "openml_task_id", "meta_REPTreeDepth2ErrRate", "meta_J48.00001.ErrRate", "meta_NBErrRate", "meta_MeanMutualInformation", "meta_NBAUC", "meta_DecisionStumpKappa", "meta_HoeffdingDDM.warnings", "meta_NoiseToSignalRatio", "meta_RandomTreeDepth3AUC_K=0", "meta_PercentageOfNumericAtts", "meta_Equiv...
[ false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, f...
1,476
363,044
mean_absolute_error
mean_absolute_error
Bioresponse
Dataset used in the tabular data benchmark https://github.com/LeoGrin/tabular-benchmark, transformed in the same way. This dataset belongs to the "classification on numerical features" benchmark. Original link: https://openml.org/d/4134 Original description: **Author**: Boehringer Ingelheim **Source**: [K...
{0: [0 - D1 (numeric)], 1: [1 - D2 (numeric)], 2: [2 - D3 (numeric)], 3: [3 - D5 (numeric)], 4: [4 - D6 (numeric)], 5: [5 - D7 (numeric)], 6: [6 - D8 (numeric)], 7: [7 - D9 (numeric)], 8: [8 - D10 (numeric)], 9: [9 - D11 (numeric)], 10: [10 - D12 (numeric)], 11: [11 - D13 (numeric)], 12: [12 - D14 (numeric)...
{'MajorityClassSize': nan, 'MaxNominalAttDistinctValues': nan, 'MinorityClassSize': nan, 'NumberOfClasses': 0.0, 'NumberOfFeatures': 420.0, 'NumberOfInstances': 3434.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 420.0, 'NumberOfSymbolicFeatures': 0.0, '...
Bioresponse
[ "D1", "D2", "D3", "D5", "D6", "D7", "D8", "D9", "D10", "D11", "D12", "D13", "D14", "D15", "D16", "D17", "D18", "D19", "D20", "D21", "D22", "D25", "D26", "D30", "D31", "D32", "D33", "D34", "D35", "D36", "D37", "D38", "D39", "D40", "D41", "D42", ...
[ false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, f...
1,477
2,930
predictive_accuracy
accuracy_score
primary-tumor
**Author**: **Source**: Unknown - **Please cite**: Citation Request: This primary tumor domain was obtained from the University Medical Centre, Institute of Oncology, Ljubljana, Yugoslavia. Thanks go to M. Zwitter and M. Soklic for providing the data. Please include this citation if you plan ...
{0: [0 - age (nominal)], 1: [1 - sex (nominal)], 2: [2 - histologic-type (nominal)], 3: [3 - degree-of-diffe (nominal)], 4: [4 - bone (nominal)], 5: [5 - bone-marrow (nominal)], 6: [6 - lung (nominal)], 7: [7 - pleura (nominal)], 8: [8 - peritoneum (nominal)], 9: [9 - liver (nominal)], 10: [10 - brain (nomina...
{'MajorityClassSize': 84.0, 'MaxNominalAttDistinctValues': 21.0, 'MinorityClassSize': 1.0, 'NumberOfClasses': 21.0, 'NumberOfFeatures': 18.0, 'NumberOfInstances': 339.0, 'NumberOfInstancesWithMissingValues': 207.0, 'NumberOfMissingValues': 225.0, 'NumberOfNumericFeatures': 0.0, 'NumberOfSymbolicFeatures': 18.0...
primary-tumor
[ "age", "sex", "histologic-type", "degree-of-diffe", "bone", "bone-marrow", "lung", "pleura", "peritoneum", "liver", "brain", "skin", "neck", "supraclavicular", "axillar", "mediastinum", "abdominal" ]
[ true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true ]
1,479
2,943
predictive_accuracy
accuracy_score
braziltourism
**Author**: **Source**: Unknown - **Please cite**: analcatdata A collection of data sets used in the book "Analyzing Categorical Data," by Jeffrey S. Simonoff, Springer-Verlag, New York, 2003. The submission consists of a zip file containing two versions of each of 84 data s...
{0: [0 - Age (numeric)], 1: [1 - Sex (nominal)], 2: [2 - Income (numeric)], 3: [3 - Travel_cost (numeric)], 4: [4 - Access_road (nominal)], 5: [5 - Active (nominal)], 6: [6 - Passive (nominal)], 7: [7 - Logged_income (numeric)], 8: [8 - Trips (nominal)]}
{'MajorityClassSize': 318.0, 'MaxNominalAttDistinctValues': 7.0, 'MinorityClassSize': 1.0, 'NumberOfClasses': 7.0, 'NumberOfFeatures': 9.0, 'NumberOfInstances': 412.0, 'NumberOfInstancesWithMissingValues': 49.0, 'NumberOfMissingValues': 96.0, 'NumberOfNumericFeatures': 4.0, 'NumberOfSymbolicFeatures': 5.0, 'c...
braziltourism
[ "Age", "Sex", "Income", "Travel_cost", "Access_road", "Active", "Passive", "Logged_income" ]
[ false, true, false, false, true, true, true, false ]
1,480
2,373
predictive_accuracy
accuracy_score
molecular-biology_promoters
**Author**: C. Harley, R. Reynolds, M. Noordewier, J. Shavlik. **Source**: [UCI](https://archive.ics.uci.edu/ml/datasets/Molecular+Biology+(Promoter+Gene+Sequences)) - 1990 **Please cite**: [UCI](https://archive.ics.uci.edu/ml/citation_policy.html) **E. coli promoter gene sequences (DNA)** Compilation of promo...
{0: [0 - class (nominal)], 1: [1 - instance (nominal)], 2: [2 - p-50 (nominal)], 3: [3 - p-49 (nominal)], 4: [4 - p-48 (nominal)], 5: [5 - p-47 (nominal)], 6: [6 - p-46 (nominal)], 7: [7 - p-45 (nominal)], 8: [8 - p-44 (nominal)], 9: [9 - p-43 (nominal)], 10: [10 - p-42 (nominal)], 11: [11 - p-41 (nominal)],...
{'MajorityClassSize': 53.0, 'MaxNominalAttDistinctValues': 4.0, 'MinorityClassSize': 53.0, 'NumberOfClasses': 2.0, 'NumberOfFeatures': 58.0, 'NumberOfInstances': 106.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 0.0, 'NumberOfSymbolicFeatures': 58.0, 'c...
molecular-biology_promoters
[ "p-50", "p-49", "p-48", "p-47", "p-46", "p-45", "p-44", "p-43", "p-42", "p-41", "p-40", "p-39", "p-38", "p-37", "p-36", "p-35", "p-34", "p-33", "p-32", "p-31", "p-30", "p-29", "p-28", "p-27", "p-26", "p-25", "p-24", "p-23", "p-22", "p-21", "p-20", "p-19"...
[ true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true...
1,481
2,923
predictive_accuracy
accuracy_score
molecular-biology_promoters
**Author**: C. Harley, R. Reynolds, M. Noordewier, J. Shavlik. **Source**: [UCI](https://archive.ics.uci.edu/ml/datasets/Molecular+Biology+(Promoter+Gene+Sequences)) - 1990 **Please cite**: [UCI](https://archive.ics.uci.edu/ml/citation_policy.html) **E. coli promoter gene sequences (DNA)** Compilation of promo...
{0: [0 - class (nominal)], 1: [1 - instance (nominal)], 2: [2 - p-50 (nominal)], 3: [3 - p-49 (nominal)], 4: [4 - p-48 (nominal)], 5: [5 - p-47 (nominal)], 6: [6 - p-46 (nominal)], 7: [7 - p-45 (nominal)], 8: [8 - p-44 (nominal)], 9: [9 - p-43 (nominal)], 10: [10 - p-42 (nominal)], 11: [11 - p-41 (nominal)],...
{'MajorityClassSize': 53.0, 'MaxNominalAttDistinctValues': 4.0, 'MinorityClassSize': 53.0, 'NumberOfClasses': 2.0, 'NumberOfFeatures': 58.0, 'NumberOfInstances': 106.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 0.0, 'NumberOfSymbolicFeatures': 58.0, 'c...
molecular-biology_promoters
[ "class", "p-50", "p-49", "p-48", "p-47", "p-46", "p-45", "p-44", "p-43", "p-42", "p-41", "p-40", "p-39", "p-38", "p-37", "p-36", "p-35", "p-34", "p-33", "p-32", "p-31", "p-30", "p-29", "p-28", "p-27", "p-26", "p-25", "p-24", "p-23", "p-22", "p-21", "p-20...
[ true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true...
1,483
2,372
predictive_accuracy
accuracy_score
lung-cancer
**Author**: **Source**: Unknown - **Please cite**: 1. Title: Lung Cancer Data 2. Source Information: - Data was published in : Hong, Z.Q. and Yang, J.Y. "Optimal Discriminant Plane for a Small Number of Samples and Design Method of Classifier on the Plane", Pattern Recognition, Vol. 24, No. ...
{0: [0 - class (nominal)], 1: [1 - attribute2 (nominal)], 2: [2 - attribute3 (nominal)], 3: [3 - attribute4 (nominal)], 4: [4 - attribute5 (nominal)], 5: [5 - attribute6 (nominal)], 6: [6 - attribute7 (nominal)], 7: [7 - attribute8 (nominal)], 8: [8 - attribute9 (nominal)], 9: [9 - attribute10 (nominal)], 10:...
{'MajorityClassSize': 13.0, 'MaxNominalAttDistinctValues': 4.0, 'MinorityClassSize': 9.0, 'NumberOfClasses': 3.0, 'NumberOfFeatures': 57.0, 'NumberOfInstances': 32.0, 'NumberOfInstancesWithMissingValues': 5.0, 'NumberOfMissingValues': 5.0, 'NumberOfNumericFeatures': 0.0, 'NumberOfSymbolicFeatures': 57.0, 'cos...
lung-cancer
[ "attribute2", "attribute3", "attribute4", "attribute5", "attribute6", "attribute7", "attribute8", "attribute9", "attribute10", "attribute11", "attribute12", "attribute13", "attribute14", "attribute15", "attribute16", "attribute17", "attribute18", "attribute19", "attribute20", "...
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1,484
2,976
predictive_accuracy
accuracy_score
meta_all.arff
null
{0: [0 - openml_task_id (numeric)], 1: [1 - meta_REPTreeDepth2ErrRate (numeric)], 2: [2 - meta_J48.00001.ErrRate (numeric)], 3: [3 - meta_NBErrRate (numeric)], 4: [4 - meta_MeanMutualInformation (numeric)], 5: [5 - meta_NBAUC (numeric)], 6: [6 - meta_DecisionStumpKappa (numeric)], 7: [7 - meta_HoeffdingDDM.warni...
{'MajorityClassSize': 42.0, 'MaxNominalAttDistinctValues': 6.0, 'MinorityClassSize': 2.0, 'NumberOfClasses': 6.0, 'NumberOfFeatures': 63.0, 'NumberOfInstances': 71.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 62.0, 'NumberOfSymbolicFeatures': 1.0, 'cos...
meta_all.arff
[ "openml_task_id", "meta_REPTreeDepth2ErrRate", "meta_J48.00001.ErrRate", "meta_NBErrRate", "meta_MeanMutualInformation", "meta_NBAUC", "meta_DecisionStumpKappa", "meta_HoeffdingDDM.warnings", "meta_NoiseToSignalRatio", "meta_RandomTreeDepth3AUC_K=0", "meta_PercentageOfNumericAtts", "meta_Equiv...
[ false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, f...
1,485
2,977
predictive_accuracy
accuracy_score
meta_batchincremental.arff
null
{0: [0 - openml_task_id (numeric)], 1: [1 - meta_REPTreeDepth2ErrRate (numeric)], 2: [2 - meta_J48.00001.ErrRate (numeric)], 3: [3 - meta_NBErrRate (numeric)], 4: [4 - meta_MeanMutualInformation (numeric)], 5: [5 - meta_NBAUC (numeric)], 6: [6 - meta_DecisionStumpKappa (numeric)], 7: [7 - meta_HoeffdingDDM.warni...
{'MajorityClassSize': 50.0, 'MaxNominalAttDistinctValues': 4.0, 'MinorityClassSize': 3.0, 'NumberOfClasses': 4.0, 'NumberOfFeatures': 63.0, 'NumberOfInstances': 74.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 62.0, 'NumberOfSymbolicFeatures': 1.0, 'cos...
meta_batchincremental.arff
[ "openml_task_id", "meta_REPTreeDepth2ErrRate", "meta_J48.00001.ErrRate", "meta_NBErrRate", "meta_MeanMutualInformation", "meta_NBAUC", "meta_DecisionStumpKappa", "meta_HoeffdingDDM.warnings", "meta_NoiseToSignalRatio", "meta_RandomTreeDepth3AUC_K=0", "meta_PercentageOfNumericAtts", "meta_Equiv...
[ false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, f...
1,486
2,938
predictive_accuracy
accuracy_score
yeast
**Author**: **Source**: Unknown - **Please cite**:
{0: [0 - mcg (numeric)], 1: [1 - gvh (numeric)], 2: [2 - alm (numeric)], 3: [3 - mit (numeric)], 4: [4 - erl (numeric)], 5: [5 - pox (numeric)], 6: [6 - vac (numeric)], 7: [7 - nuc (numeric)], 8: [8 - class_protein_localization (nominal)]}
{'MajorityClassSize': 463.0, 'MaxNominalAttDistinctValues': 10.0, 'MinorityClassSize': 5.0, 'NumberOfClasses': 10.0, 'NumberOfFeatures': 9.0, 'NumberOfInstances': 1484.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 8.0, 'NumberOfSymbolicFeatures': 1.0, '...
yeast
[ "mcg", "gvh", "alm", "mit", "erl", "pox", "vac", "nuc" ]
[ false, false, false, false, false, false, false, false ]
1,487
2,983
predictive_accuracy
accuracy_score
lung-cancer
**Author**: **Source**: Unknown - **Please cite**: 1. Title: Lung Cancer Data 2. Source Information: - Data was published in : Hong, Z.Q. and Yang, J.Y. "Optimal Discriminant Plane for a Small Number of Samples and Design Method of Classifier on the Plane", Pattern Recognition, Vol. 24, No. ...
{0: [0 - class (nominal)], 1: [1 - attribute2 (nominal)], 2: [2 - attribute3 (nominal)], 3: [3 - attribute4 (nominal)], 4: [4 - attribute5 (nominal)], 5: [5 - attribute6 (nominal)], 6: [6 - attribute7 (nominal)], 7: [7 - attribute8 (nominal)], 8: [8 - attribute9 (nominal)], 9: [9 - attribute10 (nominal)], 10:...
{'MajorityClassSize': 13.0, 'MaxNominalAttDistinctValues': 4.0, 'MinorityClassSize': 9.0, 'NumberOfClasses': 3.0, 'NumberOfFeatures': 57.0, 'NumberOfInstances': 32.0, 'NumberOfInstancesWithMissingValues': 5.0, 'NumberOfMissingValues': 5.0, 'NumberOfNumericFeatures': 0.0, 'NumberOfSymbolicFeatures': 57.0, 'cos...
lung-cancer
[ "attribute2", "attribute3", "attribute4", "attribute5", "attribute6", "attribute7", "attribute8", "attribute9", "attribute10", "attribute11", "attribute12", "attribute13", "attribute14", "attribute15", "attribute16", "attribute17", "attribute18", "attribute19", "attribute20", "...
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1,488
2,993
predictive_accuracy
accuracy_score
wine
**Author**: **Source**: Unknown - **Please cite**: 1. Title of Database: Wine recognition data Updated Sept 21, 1998 by C.Blake : Added attribute information 2. Sources: (a) Forina, M. et al, PARVUS - An Extendible Package for Data Exploration, Classification and Correlation. Institute of Pha...
{0: [0 - class (nominal)], 1: [1 - Alcohol (numeric)], 2: [2 - Malic_acid (numeric)], 3: [3 - Ash (numeric)], 4: [4 - Alcalinity_of_ash (numeric)], 5: [5 - Magnesium (numeric)], 6: [6 - Total_phenols (numeric)], 7: [7 - Flavanoids (numeric)], 8: [8 - Nonflavanoid_phenols (numeric)], 9: [9 - Proanthocyanins (nu...
{'MajorityClassSize': 71.0, 'MaxNominalAttDistinctValues': 3.0, 'MinorityClassSize': 48.0, 'NumberOfClasses': 3.0, 'NumberOfFeatures': 14.0, 'NumberOfInstances': 178.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 13.0, 'NumberOfSymbolicFeatures': 1.0, 'c...
wine
[ "Alcohol", "Malic_acid", "Ash", "Alcalinity_of_ash", "Magnesium", "Total_phenols", "Flavanoids", "Nonflavanoid_phenols", "Proanthocyanins", "Color_intensity", "Hue", "OD280%2FOD315_of_diluted_wines", "Proline" ]
[ false, false, false, false, false, false, false, false, false, false, false, false, false ]
1,489
2,942
predictive_accuracy
accuracy_score
baseball
Database of baseball players and play statistics, including 'Games_played', 'At_bats', 'Runs', 'Hits', 'Doubles', 'Triples', 'Home_runs', 'RBIs', 'Walks', 'Strikeouts', 'Batting_average', 'On_base_pct', 'Slugging_pct' and 'Fielding_ave' Notes: * Quotes, Single-Quotes and Backslashes were removed, Blanks replaced wi...
{0: [0 - Player (nominal)], 1: [1 - Number_seasons (numeric)], 2: [2 - Games_played (numeric)], 3: [3 - At_bats (numeric)], 4: [4 - Runs (numeric)], 5: [5 - Hits (numeric)], 6: [6 - Doubles (numeric)], 7: [7 - Triples (numeric)], 8: [8 - Home_runs (numeric)], 9: [9 - RBIs (numeric)], 10: [10 - Walks (numeric)...
{'MajorityClassSize': 1215.0, 'MaxNominalAttDistinctValues': 7.0, 'MinorityClassSize': 57.0, 'NumberOfClasses': 3.0, 'NumberOfFeatures': 17.0, 'NumberOfInstances': 1340.0, 'NumberOfInstancesWithMissingValues': 20.0, 'NumberOfMissingValues': 20.0, 'NumberOfNumericFeatures': 15.0, 'NumberOfSymbolicFeatures': 2.0...
baseball
[ "Number_seasons", "Games_played", "At_bats", "Runs", "Hits", "Doubles", "Triples", "Home_runs", "RBIs", "Walks", "Strikeouts", "Batting_average", "On_base_pct", "Slugging_pct", "Fielding_ave", "Position" ]
[ false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, true ]
1,490
2,979
predictive_accuracy
accuracy_score
meta_instanceincremental.arff
null
{0: [0 - openml_task_id (numeric)], 1: [1 - meta_REPTreeDepth2ErrRate (numeric)], 2: [2 - meta_J48.00001.ErrRate (numeric)], 3: [3 - meta_NBErrRate (numeric)], 4: [4 - meta_MeanMutualInformation (numeric)], 5: [5 - meta_NBAUC (numeric)], 6: [6 - meta_DecisionStumpKappa (numeric)], 7: [7 - meta_HoeffdingDDM.warni...
{'MajorityClassSize': 54.0, 'MaxNominalAttDistinctValues': 4.0, 'MinorityClassSize': 3.0, 'NumberOfClasses': 4.0, 'NumberOfFeatures': 63.0, 'NumberOfInstances': 74.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 62.0, 'NumberOfSymbolicFeatures': 1.0, 'cos...
meta_instanceincremental.arff
[ "openml_task_id", "meta_REPTreeDepth2ErrRate", "meta_J48.00001.ErrRate", "meta_NBErrRate", "meta_MeanMutualInformation", "meta_NBAUC", "meta_DecisionStumpKappa", "meta_HoeffdingDDM.warnings", "meta_NoiseToSignalRatio", "meta_RandomTreeDepth3AUC_K=0", "meta_PercentageOfNumericAtts", "meta_Equiv...
[ false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, f...
1,491
2,125
predictive_accuracy
accuracy_score
eucalyptus
**Author**: Bruce Bulloch **Source**: [WEKA Dataset Collection](http://www.cs.waikato.ac.nz/ml/weka/datasets.html) - part of the agridatasets archive. [This is the true source](http://tunedit.org/repo/Data/Agricultural/eucalyptus.arff) **Please cite**: None **Eucalyptus Soil Conservation** The objective was ...
{0: [0 - Abbrev (nominal)], 1: [1 - Rep (numeric)], 2: [2 - Locality (nominal)], 3: [3 - Map_Ref (nominal)], 4: [4 - Latitude (nominal)], 5: [5 - Altitude (numeric)], 6: [6 - Rainfall (numeric)], 7: [7 - Frosts (numeric)], 8: [8 - Year (numeric)], 9: [9 - Sp (nominal)], 10: [10 - PMCno (numeric)], 11: [11 - ...
{'MajorityClassSize': 214.0, 'MaxNominalAttDistinctValues': 27.0, 'MinorityClassSize': 105.0, 'NumberOfClasses': 5.0, 'NumberOfFeatures': 20.0, 'NumberOfInstances': 736.0, 'NumberOfInstancesWithMissingValues': 95.0, 'NumberOfMissingValues': 448.0, 'NumberOfNumericFeatures': 14.0, 'NumberOfSymbolicFeatures': 6....
eucalyptus
[ "Abbrev", "Rep", "Locality", "Map_Ref", "Latitude", "Altitude", "Rainfall", "Frosts", "Year", "Sp", "PMCno", "DBH", "Ht", "Surv", "Vig", "Ins_res", "Stem_Fm", "Crown_Fm", "Brnch_Fm" ]
[ true, false, true, true, true, false, false, false, false, true, false, false, false, false, false, false, false, false, false ]
1,492
2,978
predictive_accuracy
accuracy_score
meta_ensembles.arff
null
{0: [0 - openml_task_id (numeric)], 1: [1 - meta_REPTreeDepth2ErrRate (numeric)], 2: [2 - meta_J48.00001.ErrRate (numeric)], 3: [3 - meta_NBErrRate (numeric)], 4: [4 - meta_MeanMutualInformation (numeric)], 5: [5 - meta_NBAUC (numeric)], 6: [6 - meta_DecisionStumpKappa (numeric)], 7: [7 - meta_HoeffdingDDM.warni...
{'MajorityClassSize': 45.0, 'MaxNominalAttDistinctValues': 4.0, 'MinorityClassSize': 5.0, 'NumberOfClasses': 4.0, 'NumberOfFeatures': 63.0, 'NumberOfInstances': 74.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 62.0, 'NumberOfSymbolicFeatures': 1.0, 'cos...
meta_ensembles.arff
[ "openml_task_id", "meta_REPTreeDepth2ErrRate", "meta_J48.00001.ErrRate", "meta_NBErrRate", "meta_MeanMutualInformation", "meta_NBAUC", "meta_DecisionStumpKappa", "meta_HoeffdingDDM.warnings", "meta_NoiseToSignalRatio", "meta_RandomTreeDepth3AUC_K=0", "meta_PercentageOfNumericAtts", "meta_Equiv...
[ false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, f...
1,493
2,944
predictive_accuracy
accuracy_score
eucalyptus
**Author**: Bruce Bulloch **Source**: [WEKA Dataset Collection](http://www.cs.waikato.ac.nz/ml/weka/datasets.html) - part of the agridatasets archive. [This is the true source](http://tunedit.org/repo/Data/Agricultural/eucalyptus.arff) **Please cite**: None **Eucalyptus Soil Conservation** The objective was ...
{0: [0 - Abbrev (nominal)], 1: [1 - Rep (numeric)], 2: [2 - Locality (nominal)], 3: [3 - Map_Ref (nominal)], 4: [4 - Latitude (nominal)], 5: [5 - Altitude (numeric)], 6: [6 - Rainfall (numeric)], 7: [7 - Frosts (numeric)], 8: [8 - Year (numeric)], 9: [9 - Sp (nominal)], 10: [10 - PMCno (numeric)], 11: [11 - ...
{'MajorityClassSize': 214.0, 'MaxNominalAttDistinctValues': 27.0, 'MinorityClassSize': 105.0, 'NumberOfClasses': 5.0, 'NumberOfFeatures': 20.0, 'NumberOfInstances': 736.0, 'NumberOfInstancesWithMissingValues': 95.0, 'NumberOfMissingValues': 448.0, 'NumberOfNumericFeatures': 14.0, 'NumberOfSymbolicFeatures': 6....
eucalyptus
[ "Abbrev", "Rep", "Locality", "Map_Ref", "Latitude", "Altitude", "Rainfall", "Frosts", "Year", "Sp", "PMCno", "DBH", "Ht", "Surv", "Vig", "Ins_res", "Stem_Fm", "Crown_Fm", "Brnch_Fm" ]
[ true, false, true, true, true, false, false, false, false, true, false, false, false, false, false, false, false, false, false ]
1,494
2,984
predictive_accuracy
accuracy_score
molecular-biology_promoters
**Author**: C. Harley, R. Reynolds, M. Noordewier, J. Shavlik. **Source**: [UCI](https://archive.ics.uci.edu/ml/datasets/Molecular+Biology+(Promoter+Gene+Sequences)) - 1990 **Please cite**: [UCI](https://archive.ics.uci.edu/ml/citation_policy.html) **E. coli promoter gene sequences (DNA)** Compilation of promo...
{0: [0 - class (nominal)], 1: [1 - instance (nominal)], 2: [2 - p-50 (nominal)], 3: [3 - p-49 (nominal)], 4: [4 - p-48 (nominal)], 5: [5 - p-47 (nominal)], 6: [6 - p-46 (nominal)], 7: [7 - p-45 (nominal)], 8: [8 - p-44 (nominal)], 9: [9 - p-43 (nominal)], 10: [10 - p-42 (nominal)], 11: [11 - p-41 (nominal)],...
{'MajorityClassSize': 53.0, 'MaxNominalAttDistinctValues': 4.0, 'MinorityClassSize': 53.0, 'NumberOfClasses': 2.0, 'NumberOfFeatures': 58.0, 'NumberOfInstances': 106.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 0.0, 'NumberOfSymbolicFeatures': 58.0, 'c...
molecular-biology_promoters
[ "p-50", "p-49", "p-48", "p-47", "p-46", "p-45", "p-44", "p-43", "p-42", "p-41", "p-40", "p-39", "p-38", "p-37", "p-36", "p-35", "p-34", "p-33", "p-32", "p-31", "p-30", "p-29", "p-28", "p-27", "p-26", "p-25", "p-24", "p-23", "p-22", "p-21", "p-20", "p-19"...
[ true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true...
1,495
3,026
predictive_accuracy
accuracy_score
shuttle-landing-control
# Space Shuttle Autolanding Domain NASA: Mr. Roger Burke's autolander design team ##### Past Usage: (several, it appears) Example: Michie,D. (1988). The Fifth Generation's Unbridged Gap. In Rolf Herken (Ed.) The Universal Turing Machine: A Half-Century Survey, 466-489, Oxford Uni...
{0: [0 - Class (nominal)], 1: [1 - STABILITY (nominal)], 2: [2 - ERROR (nominal)], 3: [3 - SIGN (nominal)], 4: [4 - WIND (nominal)], 5: [5 - MAGNITUDE (nominal)], 6: [6 - VISIBILITY (nominal)]}
{'MajorityClassSize': 9.0, 'MaxNominalAttDistinctValues': 4.0, 'MinorityClassSize': 6.0, 'NumberOfClasses': 2.0, 'NumberOfFeatures': 7.0, 'NumberOfInstances': 15.0, 'NumberOfInstancesWithMissingValues': 9.0, 'NumberOfMissingValues': 26.0, 'NumberOfNumericFeatures': 0.0, 'NumberOfSymbolicFeatures': 7.0, 'cost_...
shuttle-landing-control
[ "STABILITY", "ERROR", "SIGN", "WIND", "MAGNITUDE", "VISIBILITY" ]
[ true, true, true, true, true, true ]
1,496
2,982
predictive_accuracy
accuracy_score
flags
**Author**: Richard S. Forsyth **Source**: Unknown - 5/15/1990 **Please cite**: ARFF version of UCI dataset 'flags'. Creators: Collected primarily from the "Collins Gem Guide to Flags": Collins Publishers (1986). Donor: Richard S. Forsyth. Date 5/15/1990 This data file contains details of various nations and ...
{0: [0 - name (nominal)], 1: [1 - 1landmass (nominal)], 2: [2 - 2zone (nominal)], 3: [3 - 3area (numeric)], 4: [4 - population (numeric)], 5: [5 - language (nominal)], 6: [6 - religion (nominal)], 7: [7 - bars (nominal)], 8: [8 - stripes (nominal)], 9: [9 - colours (nominal)], 10: [10 - red (nominal)], 11: [...
{'MajorityClassSize': 60.0, 'MaxNominalAttDistinctValues': 14.0, 'MinorityClassSize': 4.0, 'NumberOfClasses': 8.0, 'NumberOfFeatures': 29.0, 'NumberOfInstances': 194.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 2.0, 'NumberOfSymbolicFeatures': 27.0, 'c...
flags
[ "1landmass", "2zone", "3area", "population", "language", "bars", "stripes", "colours", "red", "green", "blue", "gold", "white", "black", "orange", "mainhue", "circles", "crosses", "saltires", "quarters", "sunstars", "crescent", "triangle", "icon", "animate", "text",...
[ true, true, false, false, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true ]
1,497
3,012
predictive_accuracy
accuracy_score
shuttle-landing-control
# Space Shuttle Autolanding Domain NASA: Mr. Roger Burke's autolander design team ##### Past Usage: (several, it appears) Example: Michie,D. (1988). The Fifth Generation's Unbridged Gap. In Rolf Herken (Ed.) The Universal Turing Machine: A Half-Century Survey, 466-489, Oxford Uni...
{0: [0 - Class (nominal)], 1: [1 - STABILITY (nominal)], 2: [2 - ERROR (nominal)], 3: [3 - SIGN (nominal)], 4: [4 - WIND (nominal)], 5: [5 - MAGNITUDE (nominal)], 6: [6 - VISIBILITY (nominal)]}
{'MajorityClassSize': 9.0, 'MaxNominalAttDistinctValues': 4.0, 'MinorityClassSize': 6.0, 'NumberOfClasses': 2.0, 'NumberOfFeatures': 7.0, 'NumberOfInstances': 15.0, 'NumberOfInstancesWithMissingValues': 9.0, 'NumberOfMissingValues': 26.0, 'NumberOfNumericFeatures': 0.0, 'NumberOfSymbolicFeatures': 7.0, 'cost_...
shuttle-landing-control
[ "STABILITY", "ERROR", "SIGN", "WIND", "MAGNITUDE", "VISIBILITY" ]
[ true, true, true, true, true, true ]
1,498
2,940
predictive_accuracy
accuracy_score
abalone
**Author**: **Source**: Unknown - **Please cite**: 1. Title of Database: Abalone data 2. Sources: (a) Original owners of database: Marine Resources Division Marine Research Laboratories - Taroona Department of Primary Industry and Fisheries, Tasmania GPO Box 619F, Hobart, Tasmania 7001, Austr...
{0: [0 - Sex (nominal)], 1: [1 - Length (numeric)], 2: [2 - Diameter (numeric)], 3: [3 - Height (numeric)], 4: [4 - Whole_weight (numeric)], 5: [5 - Shucked_weight (numeric)], 6: [6 - Viscera_weight (numeric)], 7: [7 - Shell_weight (numeric)], 8: [8 - Class_number_of_rings (nominal)]}
{'MajorityClassSize': 689.0, 'MaxNominalAttDistinctValues': 28.0, 'MinorityClassSize': 1.0, 'NumberOfClasses': 28.0, 'NumberOfFeatures': 9.0, 'NumberOfInstances': 4177.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 7.0, 'NumberOfSymbolicFeatures': 2.0, '...
abalone
[ "Sex", "Length", "Diameter", "Height", "Whole_weight", "Shucked_weight", "Viscera_weight", "Shell_weight" ]
[ true, false, false, false, false, false, false, false ]
1,499
3,018
predictive_accuracy
accuracy_score
flags
**Author**: Richard S. Forsyth **Source**: Unknown - 5/15/1990 **Please cite**: ARFF version of UCI dataset 'flags'. Creators: Collected primarily from the "Collins Gem Guide to Flags": Collins Publishers (1986). Donor: Richard S. Forsyth. Date 5/15/1990 This data file contains details of various nations and ...
{0: [0 - name (nominal)], 1: [1 - 1landmass (nominal)], 2: [2 - 2zone (nominal)], 3: [3 - 3area (numeric)], 4: [4 - population (numeric)], 5: [5 - language (nominal)], 6: [6 - religion (nominal)], 7: [7 - bars (nominal)], 8: [8 - stripes (nominal)], 9: [9 - colours (nominal)], 10: [10 - red (nominal)], 11: [...
{'MajorityClassSize': 60.0, 'MaxNominalAttDistinctValues': 14.0, 'MinorityClassSize': 4.0, 'NumberOfClasses': 8.0, 'NumberOfFeatures': 29.0, 'NumberOfInstances': 194.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 2.0, 'NumberOfSymbolicFeatures': 27.0, 'c...
flags
[ "1landmass", "2zone", "3area", "population", "language", "bars", "stripes", "colours", "red", "green", "blue", "gold", "white", "black", "orange", "mainhue", "circles", "crosses", "saltires", "quarters", "sunstars", "crescent", "triangle", "icon", "animate", "text",...
[ true, true, false, false, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true ]
1,501
1,953
predictive_accuracy
accuracy_score
mfeat-factors
**Author**: Robert P.W. Duin, Department of Applied Physics, Delft University of Technology **Source**: [UCI](https://archive.ics.uci.edu/ml/datasets/Multiple+Features) - 1998 **Please cite**: [UCI](https://archive.ics.uci.edu/ml/citation_policy.html) **Multiple Features Dataset: Factors** One of a set of 6 d...
{0: [0 - att1 (numeric)], 1: [1 - att2 (numeric)], 2: [2 - att3 (numeric)], 3: [3 - att4 (numeric)], 4: [4 - att5 (numeric)], 5: [5 - att6 (numeric)], 6: [6 - att7 (numeric)], 7: [7 - att8 (numeric)], 8: [8 - att9 (numeric)], 9: [9 - att10 (numeric)], 10: [10 - att11 (numeric)], 11: [11 - att12 (numeric)], ...
{'MajorityClassSize': 200.0, 'MaxNominalAttDistinctValues': 10.0, 'MinorityClassSize': 200.0, 'NumberOfClasses': 10.0, 'NumberOfFeatures': 217.0, 'NumberOfInstances': 2000.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 216.0, 'NumberOfSymbolicFeatures': 1...
mfeat-factors
[ "att1", "att2", "att3", "att4", "att5", "att6", "att7", "att8", "att9", "att10", "att11", "att12", "att13", "att14", "att15", "att16", "att17", "att18", "att19", "att20", "att21", "att22", "att23", "att24", "att25", "att26", "att27", "att28", "att29", "att30...
[ false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, f...
1,502
3,052
predictive_accuracy
accuracy_score
hayes-roth
**Author**: Barbara and Frederick Hayes-Roth **Source**: [original](https://archive.ics.uci.edu/ml/datasets/Hayes-Roth) - **Please cite**: Hayes-Roth Database This is a merged version of the separate train and test set which are usually distributed. On OpenML this train-test split can be found as one of th...
{0: [0 - hobby (numeric)], 1: [1 - age (numeric)], 2: [2 - educational_level (numeric)], 3: [3 - marital_status (numeric)], 4: [4 - class (nominal)]}
{'MajorityClassSize': 65.0, 'MaxNominalAttDistinctValues': 3.0, 'MinorityClassSize': 31.0, 'NumberOfClasses': 3.0, 'NumberOfFeatures': 5.0, 'NumberOfInstances': 160.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 4.0, 'NumberOfSymbolicFeatures': 1.0, 'cos...
hayes-roth
[ "hobby", "age", "educational_level", "marital_status" ]
[ false, false, false, false ]
1,504
3,046
predictive_accuracy
accuracy_score
flags
**Author**: Richard S. Forsyth **Source**: Unknown - 5/15/1990 **Please cite**: ARFF version of UCI dataset 'flags'. Creators: Collected primarily from the "Collins Gem Guide to Flags": Collins Publishers (1986). Donor: Richard S. Forsyth. Date 5/15/1990 This data file contains details of various nations and ...
{0: [0 - name (nominal)], 1: [1 - 1landmass (nominal)], 2: [2 - 2zone (nominal)], 3: [3 - 3area (numeric)], 4: [4 - population (numeric)], 5: [5 - language (nominal)], 6: [6 - religion (nominal)], 7: [7 - bars (nominal)], 8: [8 - stripes (nominal)], 9: [9 - colours (nominal)], 10: [10 - red (nominal)], 11: [...
{'MajorityClassSize': 60.0, 'MaxNominalAttDistinctValues': 14.0, 'MinorityClassSize': 4.0, 'NumberOfClasses': 8.0, 'NumberOfFeatures': 29.0, 'NumberOfInstances': 194.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 2.0, 'NumberOfSymbolicFeatures': 27.0, 'c...
flags
[ "1landmass", "2zone", "3area", "population", "language", "bars", "stripes", "colours", "red", "green", "blue", "gold", "white", "black", "orange", "mainhue", "circles", "crosses", "saltires", "quarters", "sunstars", "crescent", "triangle", "icon", "animate", "text",...
[ true, true, false, false, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true ]
1,505
3,045
predictive_accuracy
accuracy_score
wine
**Author**: **Source**: Unknown - **Please cite**: 1. Title of Database: Wine recognition data Updated Sept 21, 1998 by C.Blake : Added attribute information 2. Sources: (a) Forina, M. et al, PARVUS - An Extendible Package for Data Exploration, Classification and Correlation. Institute of Pha...
{0: [0 - class (nominal)], 1: [1 - Alcohol (numeric)], 2: [2 - Malic_acid (numeric)], 3: [3 - Ash (numeric)], 4: [4 - Alcalinity_of_ash (numeric)], 5: [5 - Magnesium (numeric)], 6: [6 - Total_phenols (numeric)], 7: [7 - Flavanoids (numeric)], 8: [8 - Nonflavanoid_phenols (numeric)], 9: [9 - Proanthocyanins (nu...
{'MajorityClassSize': 71.0, 'MaxNominalAttDistinctValues': 3.0, 'MinorityClassSize': 48.0, 'NumberOfClasses': 3.0, 'NumberOfFeatures': 14.0, 'NumberOfInstances': 178.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 13.0, 'NumberOfSymbolicFeatures': 1.0, 'c...
wine
[ "Alcohol", "Malic_acid", "Ash", "Alcalinity_of_ash", "Magnesium", "Total_phenols", "Flavanoids", "Nonflavanoid_phenols", "Proanthocyanins", "Color_intensity", "Hue", "OD280%2FOD315_of_diluted_wines", "Proline" ]
[ false, false, false, false, false, false, false, false, false, false, false, false, false ]
1,506
3,053
predictive_accuracy
accuracy_score
monks-problems-1
**Author**: Sebastian Thrun (Carnegie Mellon University) **Source**: [UCI](https://archive.ics.uci.edu/ml/datasets/MONK's+Problems) - October 1992 **Please cite**: [UCI](https://archive.ics.uci.edu/ml/citation_policy.html) **The Monk's Problems: Problem 1** Once upon a time, in July 1991, the monks of Corsend...
{0: [0 - class (nominal)], 1: [1 - attr1 (nominal)], 2: [2 - attr2 (nominal)], 3: [3 - attr3 (nominal)], 4: [4 - attr4 (nominal)], 5: [5 - attr5 (nominal)], 6: [6 - attr6 (nominal)]}
{'MajorityClassSize': 278.0, 'MaxNominalAttDistinctValues': 4.0, 'MinorityClassSize': 278.0, 'NumberOfClasses': 2.0, 'NumberOfFeatures': 7.0, 'NumberOfInstances': 556.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 0.0, 'NumberOfSymbolicFeatures': 7.0, 'c...
monks-problems-1
[ "attr1", "attr2", "attr3", "attr4", "attr5", "attr6" ]
[ true, true, true, true, true, true ]
1,509
3,055
predictive_accuracy
accuracy_score
monks-problems-3
**Author**: Sebastian Thrun (Carnegie Mellon University) **Source**: [UCI](https://archive.ics.uci.edu/ml/datasets/MONK's+Problems) - October 1992 **Please cite**: [UCI](https://archive.ics.uci.edu/ml/citation_policy.html) **The Monk's Problems: Problem 3** Once upon a time, in July 1991, the monks of Corsend...
{0: [0 - class (nominal)], 1: [1 - attr1 (nominal)], 2: [2 - attr2 (nominal)], 3: [3 - attr3 (nominal)], 4: [4 - attr4 (nominal)], 5: [5 - attr5 (nominal)], 6: [6 - attr6 (nominal)]}
{'MajorityClassSize': 288.0, 'MaxNominalAttDistinctValues': 4.0, 'MinorityClassSize': 266.0, 'NumberOfClasses': 2.0, 'NumberOfFeatures': 7.0, 'NumberOfInstances': 554.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 0.0, 'NumberOfSymbolicFeatures': 7.0, 'c...
monks-problems-3
[ "attr1", "attr2", "attr3", "attr4", "attr5", "attr6" ]
[ true, true, true, true, true, true ]
1,512
3,064
predictive_accuracy
accuracy_score
aids
**Author**: Jeffrey S. Simonoff **Source**: [original](http://www.stern.nyu.edu/~jsimonof/AnalCatData) - **Please cite**: Jeffrey S. Simonoff. Analyzing Categorical Data, Springer-Verlag, New York, 2003 Data originating from the book "Analyzing Categorical Data" by Jeffrey S. Simonoff.
{0: [0 - Sex (nominal)], 1: [1 - Age (nominal)], 2: [2 - Race (nominal)], 3: [3 - AIDS (numeric)], 4: [4 - Total (numeric)]}
{'MajorityClassSize': 25.0, 'MaxNominalAttDistinctValues': 5.0, 'MinorityClassSize': 25.0, 'NumberOfClasses': 2.0, 'NumberOfFeatures': 5.0, 'NumberOfInstances': 50.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 2.0, 'NumberOfSymbolicFeatures': 3.0, 'cost...
aids
[ "Age", "Race", "AIDS", "Total" ]
[ true, true, false, false ]
1,513
3,054
predictive_accuracy
accuracy_score
monks-problems-2
**Author**: Sebastian Thrun (Carnegie Mellon University) **Source**: [UCI](https://archive.ics.uci.edu/ml/datasets/MONK's+Problems) - October 1992 **Please cite**: [UCI](https://archive.ics.uci.edu/ml/citation_policy.html) **The Monk's Problems: Problem 2** Once upon a time, in July 1991, the monks of Corsend...
{0: [0 - class (nominal)], 1: [1 - attr1 (nominal)], 2: [2 - attr2 (nominal)], 3: [3 - attr3 (nominal)], 4: [4 - attr4 (nominal)], 5: [5 - attr5 (nominal)], 6: [6 - attr6 (nominal)]}
{'MajorityClassSize': 395.0, 'MaxNominalAttDistinctValues': 4.0, 'MinorityClassSize': 206.0, 'NumberOfClasses': 2.0, 'NumberOfFeatures': 7.0, 'NumberOfInstances': 601.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 0.0, 'NumberOfSymbolicFeatures': 7.0, 'c...
monks-problems-2
[ "attr1", "attr2", "attr3", "attr4", "attr5", "attr6" ]
[ true, true, true, true, true, true ]
1,514
3,062
predictive_accuracy
accuracy_score
white-clover
**Author**: Ian Tarbotton **Source**: [original](http://www.cs.waikato.ac.nz/ml/weka/datasets.html) - **Please cite**: White Clover Persistence Trials Data source: Ian Tarbotton AgResearch, Whatawhata Research Centre, Hamilton, New Zealand The objective was to determine the mechanisms which influence the p...
{0: [0 - strata (nominal)], 1: [1 - plot (nominal)], 2: [2 - paddock (nominal)], 3: [3 - WhiteClover-91 (numeric)], 4: [4 - BareGround-91 (numeric)], 5: [5 - Cocksfoot-91 (numeric)], 6: [6 - OtherGrasses-91 (numeric)], 7: [7 - OtherLegumes-91 (numeric)], 8: [8 - RyeGrass-91 (numeric)], 9: [9 - Weeds-91 (numeri...
{'MajorityClassSize': 38.0, 'MaxNominalAttDistinctValues': 7.0, 'MinorityClassSize': 1.0, 'NumberOfClasses': 4.0, 'NumberOfFeatures': 32.0, 'NumberOfInstances': 63.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 27.0, 'NumberOfSymbolicFeatures': 5.0, 'cos...
white-clover
[ "strata", "plot", "paddock", "WhiteClover-91", "BareGround-91", "Cocksfoot-91", "OtherGrasses-91", "OtherLegumes-91", "RyeGrass-91", "Weeds-91", "WhiteClover-92", "BareGround-92", "Cocksfoot-92", "OtherGrasses-92", "OtherLegumes-92", "RyeGrass-92", "Weeds-92", "WhiteClover-93", "...
[ true, true, true, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, true ]
1,515
3,058
predictive_accuracy
accuracy_score
grub-damage
**Author**: R. J. Townsend **Source**: [original](http://www.cs.waikato.ac.nz/ml/weka/datasets.html) - **Please cite**: Grass Grubs and Damage Ranking Data source: R. J. Townsend AgResearch, Lincoln, New Zealand Grass grubs are one of the major insect pests of pasture in Canterbury and can cause severe pa...
{0: [0 - year_zone (nominal)], 1: [1 - year (nominal)], 2: [2 - strip (numeric)], 3: [3 - pdk (numeric)], 4: [4 - damage_rankRJT (nominal)], 5: [5 - damage_rankALL (nominal)], 6: [6 - dry_or_irr (nominal)], 7: [7 - zone (nominal)], 8: [8 - GG_new (nominal)]}
{'MajorityClassSize': 49.0, 'MaxNominalAttDistinctValues': 21.0, 'MinorityClassSize': 19.0, 'NumberOfClasses': 4.0, 'NumberOfFeatures': 9.0, 'NumberOfInstances': 155.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 2.0, 'NumberOfSymbolicFeatures': 7.0, 'co...
grub-damage
[ "year_zone", "year", "strip", "pdk", "damage_rankRJT", "damage_rankALL", "dry_or_irr", "zone" ]
[ true, true, false, false, true, true, true, true ]
1,516
3,056
predictive_accuracy
accuracy_score
SPECT
**Author**: Krzysztof J. Cios","Lukasz A. **Source**: [original](https://archive.ics.uci.edu/ml/datasets/SPECT+Heart) - **Please cite**: SPECT heart data This is a merged version of the separate train and test set which are usually distributed. On OpenML this train-test split can be found as one of the possib...
{0: [0 - OVERALL_DIAGNOSIS (nominal)], 1: [1 - F1 (nominal)], 2: [2 - F2 (nominal)], 3: [3 - F3 (nominal)], 4: [4 - F4 (nominal)], 5: [5 - F5 (nominal)], 6: [6 - F6 (nominal)], 7: [7 - F7 (nominal)], 8: [8 - F8 (nominal)], 9: [9 - F9 (nominal)], 10: [10 - F10 (nominal)], 11: [11 - F11 (nominal)], 12: [12 - ...
{'MajorityClassSize': 212.0, 'MaxNominalAttDistinctValues': 2.0, 'MinorityClassSize': 55.0, 'NumberOfClasses': 2.0, 'NumberOfFeatures': 23.0, 'NumberOfInstances': 267.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 0.0, 'NumberOfSymbolicFeatures': 23.0, '...
SPECT
[ "F1", "F2", "F3", "F4", "F5", "F6", "F7", "F8", "F9", "F10", "F11", "F12", "F13", "F14", "F15", "F16", "F17", "F18", "F19", "F20", "F21", "F22" ]
[ true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true ]
1,517
2,120
predictive_accuracy
accuracy_score
satimage
**Author**: Ashwin Srinivasan, Department of Statistics and Data Modeling, University of Strathclyde **Source**: [UCI](https://archive.ics.uci.edu/ml/datasets/Statlog+(Landsat+Satellite)) - 1993 **Please cite**: [UCI](https://archive.ics.uci.edu/ml/citation_policy.html) The database consists of the multi-spectra...
{0: [0 - Aattr (numeric)], 1: [1 - Battr (numeric)], 2: [2 - Cattr (numeric)], 3: [3 - Dattr (numeric)], 4: [4 - Eattr (numeric)], 5: [5 - Fattr (numeric)], 6: [6 - A1attr (numeric)], 7: [7 - B2attr (numeric)], 8: [8 - C3attr (numeric)], 9: [9 - D4attr (numeric)], 10: [10 - E5attr (numeric)], 11: [11 - F6att...
{'MajorityClassSize': 1531.0, 'MaxNominalAttDistinctValues': 6.0, 'MinorityClassSize': 625.0, 'NumberOfClasses': 6.0, 'NumberOfFeatures': 37.0, 'NumberOfInstances': 6430.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 36.0, 'NumberOfSymbolicFeatures': 1.0,...
satimage
[ "Aattr", "Battr", "Cattr", "Dattr", "Eattr", "Fattr", "A1attr", "B2attr", "C3attr", "D4attr", "E5attr", "F6attr", "A7attr", "B8attr", "C9attr", "D10attr", "E11attr", "F12attr", "A13attr", "B14attr", "C15attr", "D16attr", "E17attr", "F18attr", "A19attr", "B20attr", ...
[ false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, f...
1,518
3,011
predictive_accuracy
accuracy_score
hypothyroid
**Author**: **Source**: Unknown - **Please cite**: ; ; Thyroid disease records supplied by the Garavan Institute and J. Ross ; Quinlan, New South Wales Institute, Syndney, Australia. ; ; 1987. ; hypothyroid, primary hypothyroid, compensated hypothyroid, secondary hypothyroid, negative. | classes ...
{0: [0 - age (numeric)], 1: [1 - sex (nominal)], 2: [2 - on_thyroxine (nominal)], 3: [3 - query_on_thyroxine (nominal)], 4: [4 - on_antithyroid_medication (nominal)], 5: [5 - sick (nominal)], 6: [6 - pregnant (nominal)], 7: [7 - thyroid_surgery (nominal)], 8: [8 - I131_treatment (nominal)], 9: [9 - query_hypot...
{'MajorityClassSize': 3481.0, 'MaxNominalAttDistinctValues': 5.0, 'MinorityClassSize': 2.0, 'NumberOfClasses': 4.0, 'NumberOfFeatures': 30.0, 'NumberOfInstances': 3772.0, 'NumberOfInstancesWithMissingValues': 3772.0, 'NumberOfMissingValues': 6064.0, 'NumberOfNumericFeatures': 7.0, 'NumberOfSymbolicFeatures': 2...
hypothyroid
[ "age", "sex", "on_thyroxine", "query_on_thyroxine", "on_antithyroid_medication", "sick", "pregnant", "thyroid_surgery", "I131_treatment", "query_hypothyroid", "query_hyperthyroid", "lithium", "goitre", "tumor", "hypopituitary", "psych", "TSH_measured", "TSH", "T3_measured", "T3...
[ false, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, false, true, false, true, false, true, false, true, false, true, false, true ]
1,520
3,061
predictive_accuracy
accuracy_score
squash-unstored
**Author**: Winna Harvey **Source**: [original](http://www.cs.waikato.ac.nz/ml/weka/datasets.html) - **Please cite**: Squash Harvest Unstored Data source: Winna Harvey Crop and Food Research, Christchurch, New Zealand The purpose of the research was to determine the changes taking place in squash fruit durin...
{0: [0 - site (nominal)], 1: [1 - daf (nominal)], 2: [2 - fruit (nominal)], 3: [3 - weight (numeric)], 4: [4 - pene (numeric)], 5: [5 - solids (numeric)], 6: [6 - brix (numeric)], 7: [7 - a* (numeric)], 8: [8 - egdd (numeric)], 9: [9 - fgdd (numeric)], 10: [10 - groundspot_a* (numeric)], 11: [11 - glucose (n...
{'MajorityClassSize': 24.0, 'MaxNominalAttDistinctValues': 22.0, 'MinorityClassSize': 4.0, 'NumberOfClasses': 3.0, 'NumberOfFeatures': 24.0, 'NumberOfInstances': 52.0, 'NumberOfInstancesWithMissingValues': 9.0, 'NumberOfMissingValues': 39.0, 'NumberOfNumericFeatures': 20.0, 'NumberOfSymbolicFeatures': 4.0, 'c...
squash-unstored
[ "site", "daf", "fruit", "weight", "pene", "solids", "brix", "a*", "egdd", "fgdd", "groundspot_a*", "glucose", "fructose", "sucrose", "total", "glucose+fructose", "starch", "sweetness", "flavour", "dry/moist", "fibre", "heat_input_emerg", "heat_input_flower" ]
[ true, true, true, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false ]
1,521
3,501
predictive_accuracy
accuracy_score
white-clover
**Author**: Ian Tarbotton **Source**: [original](http://www.cs.waikato.ac.nz/ml/weka/datasets.html) - **Please cite**: White Clover Persistence Trials Data source: Ian Tarbotton AgResearch, Whatawhata Research Centre, Hamilton, New Zealand The objective was to determine the mechanisms which influence the p...
{0: [0 - strata (nominal)], 1: [1 - plot (nominal)], 2: [2 - paddock (nominal)], 3: [3 - WhiteClover-91 (numeric)], 4: [4 - BareGround-91 (numeric)], 5: [5 - Cocksfoot-91 (numeric)], 6: [6 - OtherGrasses-91 (numeric)], 7: [7 - OtherLegumes-91 (numeric)], 8: [8 - RyeGrass-91 (numeric)], 9: [9 - Weeds-91 (numeri...
{'MajorityClassSize': 38.0, 'MaxNominalAttDistinctValues': 7.0, 'MinorityClassSize': 1.0, 'NumberOfClasses': 4.0, 'NumberOfFeatures': 32.0, 'NumberOfInstances': 63.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 27.0, 'NumberOfSymbolicFeatures': 5.0, 'cos...
white-clover
[ "strata", "plot", "paddock", "WhiteClover-91", "BareGround-91", "Cocksfoot-91", "OtherGrasses-91", "OtherLegumes-91", "RyeGrass-91", "Weeds-91", "WhiteClover-92", "BareGround-92", "Cocksfoot-92", "OtherGrasses-92", "OtherLegumes-92", "RyeGrass-92", "Weeds-92", "WhiteClover-93", "...
[ true, true, true, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, true ]
1,522
3,059
predictive_accuracy
accuracy_score
pasture
**Author**: Dave Barker **Source**: [original](http://www.cs.waikato.ac.nz/ml/weka/datasets.html) - **Please cite**: Pasture Production Data source: Dave Barker AgResearch Grasslands, Palmerston North, New Zealand The objective was to predict pasture production from a variety of biophysical factors. Vegeta...
{0: [0 - fertiliser (nominal)], 1: [1 - slope (numeric)], 2: [2 - aspect-dev-NW (numeric)], 3: [3 - OlsenP (numeric)], 4: [4 - MinN (numeric)], 5: [5 - TS (numeric)], 6: [6 - Ca-Mg (numeric)], 7: [7 - LOM (numeric)], 8: [8 - NFIX-mean (numeric)], 9: [9 - Eworms-main-3 (numeric)], 10: [10 - Eworms-No-species (...
{'MajorityClassSize': 12.0, 'MaxNominalAttDistinctValues': 4.0, 'MinorityClassSize': 12.0, 'NumberOfClasses': 3.0, 'NumberOfFeatures': 23.0, 'NumberOfInstances': 36.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 21.0, 'NumberOfSymbolicFeatures': 2.0, 'co...
pasture
[ "fertiliser", "slope", "aspect-dev-NW", "OlsenP", "MinN", "TS", "Ca-Mg", "LOM", "NFIX-mean", "Eworms-main-3", "Eworms-No-species", "KUnSat", "OM", "Air-Perm", "Porosity", "HFRG-pct-mean", "legume-yield", "OSPP-pct-mean", "Jan-Mar-mean-TDR", "Annual-Mean-Runoff", "root-surface...
[ true, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false ]
1,523
3,503
predictive_accuracy
accuracy_score
aids
**Author**: Jeffrey S. Simonoff **Source**: [original](http://www.stern.nyu.edu/~jsimonof/AnalCatData) - **Please cite**: Jeffrey S. Simonoff. Analyzing Categorical Data, Springer-Verlag, New York, 2003 Data originating from the book "Analyzing Categorical Data" by Jeffrey S. Simonoff.
{0: [0 - Sex (nominal)], 1: [1 - Age (nominal)], 2: [2 - Race (nominal)], 3: [3 - AIDS (numeric)], 4: [4 - Total (numeric)]}
{'MajorityClassSize': 25.0, 'MaxNominalAttDistinctValues': 5.0, 'MinorityClassSize': 25.0, 'NumberOfClasses': 2.0, 'NumberOfFeatures': 5.0, 'NumberOfInstances': 50.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 2.0, 'NumberOfSymbolicFeatures': 3.0, 'cost...
aids
[ "Age", "Race", "AIDS", "Total" ]
[ true, true, false, false ]
1,524
1,892
predictive_accuracy
accuracy_score
mfeat-factors
**Author**: Robert P.W. Duin, Department of Applied Physics, Delft University of Technology **Source**: [UCI](https://archive.ics.uci.edu/ml/datasets/Multiple+Features) - 1998 **Please cite**: [UCI](https://archive.ics.uci.edu/ml/citation_policy.html) **Multiple Features Dataset: Factors** One of a set of 6 d...
{0: [0 - att1 (numeric)], 1: [1 - att2 (numeric)], 2: [2 - att3 (numeric)], 3: [3 - att4 (numeric)], 4: [4 - att5 (numeric)], 5: [5 - att6 (numeric)], 6: [6 - att7 (numeric)], 7: [7 - att8 (numeric)], 8: [8 - att9 (numeric)], 9: [9 - att10 (numeric)], 10: [10 - att11 (numeric)], 11: [11 - att12 (numeric)], ...
{'MajorityClassSize': 200.0, 'MaxNominalAttDistinctValues': 10.0, 'MinorityClassSize': 200.0, 'NumberOfClasses': 10.0, 'NumberOfFeatures': 217.0, 'NumberOfInstances': 2000.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 216.0, 'NumberOfSymbolicFeatures': 1...
mfeat-factors
[ "att1", "att2", "att3", "att4", "att5", "att6", "att7", "att8", "att9", "att10", "att11", "att12", "att13", "att14", "att15", "att16", "att17", "att18", "att19", "att20", "att21", "att22", "att23", "att24", "att25", "att26", "att27", "att28", "att29", "att30...
[ false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, f...
1,525
3,495
predictive_accuracy
accuracy_score
SPECT
**Author**: Krzysztof J. Cios","Lukasz A. **Source**: [original](https://archive.ics.uci.edu/ml/datasets/SPECT+Heart) - **Please cite**: SPECT heart data This is a merged version of the separate train and test set which are usually distributed. On OpenML this train-test split can be found as one of the possib...
{0: [0 - OVERALL_DIAGNOSIS (nominal)], 1: [1 - F1 (nominal)], 2: [2 - F2 (nominal)], 3: [3 - F3 (nominal)], 4: [4 - F4 (nominal)], 5: [5 - F5 (nominal)], 6: [6 - F6 (nominal)], 7: [7 - F7 (nominal)], 8: [8 - F8 (nominal)], 9: [9 - F9 (nominal)], 10: [10 - F10 (nominal)], 11: [11 - F11 (nominal)], 12: [12 - ...
{'MajorityClassSize': 212.0, 'MaxNominalAttDistinctValues': 2.0, 'MinorityClassSize': 55.0, 'NumberOfClasses': 2.0, 'NumberOfFeatures': 23.0, 'NumberOfInstances': 267.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 0.0, 'NumberOfSymbolicFeatures': 23.0, '...
SPECT
[ "F1", "F2", "F3", "F4", "F5", "F6", "F7", "F8", "F9", "F10", "F11", "F12", "F13", "F14", "F15", "F16", "F17", "F18", "F19", "F20", "F21", "F22" ]
[ true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true ]
1,527
3,057
predictive_accuracy
accuracy_score
SPECTF
**Author**: Krzysztof J. Cios","Lukasz A. **Source**: [original](https://archive.ics.uci.edu/ml/datasets/SPECTF+Heart) - **Please cite**: SPECTF heart data This is a merged version of the separate train and test set which are usually distributed. On OpenML this train-test split can be found as one of the poss...
{0: [0 - OVERALL_DIAGNOSIS (nominal)], 1: [1 - F1R (numeric)], 2: [2 - F1S (numeric)], 3: [3 - F2R (numeric)], 4: [4 - F2S (numeric)], 5: [5 - F3R (numeric)], 6: [6 - F3S (numeric)], 7: [7 - F4R (numeric)], 8: [8 - F4S (numeric)], 9: [9 - F5R (numeric)], 10: [10 - F5S (numeric)], 11: [11 - F6R (numeric)], 1...
{'MajorityClassSize': 254.0, 'MaxNominalAttDistinctValues': 2.0, 'MinorityClassSize': 95.0, 'NumberOfClasses': 2.0, 'NumberOfFeatures': 45.0, 'NumberOfInstances': 349.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 44.0, 'NumberOfSymbolicFeatures': 1.0, '...
SPECTF
[ "F1R", "F1S", "F2R", "F2S", "F3R", "F3S", "F4R", "F4S", "F5R", "F5S", "F6R", "F6S", "F7R", "F7S", "F8R", "F8S", "F9R", "F9S", "F10R", "F10S", "F11R", "F11S", "F12R", "F12S", "F13R", "F13S", "F14R", "F14S", "F15R", "F15S", "F16R", "F16S", "F17R", "F17...
[ false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, f...
1,528
3,491
predictive_accuracy
accuracy_score
hayes-roth
**Author**: Barbara and Frederick Hayes-Roth **Source**: [original](https://archive.ics.uci.edu/ml/datasets/Hayes-Roth) - **Please cite**: Hayes-Roth Database This is a merged version of the separate train and test set which are usually distributed. On OpenML this train-test split can be found as one of th...
{0: [0 - hobby (numeric)], 1: [1 - age (numeric)], 2: [2 - educational_level (numeric)], 3: [3 - marital_status (numeric)], 4: [4 - class (nominal)]}
{'MajorityClassSize': 65.0, 'MaxNominalAttDistinctValues': 3.0, 'MinorityClassSize': 31.0, 'NumberOfClasses': 3.0, 'NumberOfFeatures': 5.0, 'NumberOfInstances': 160.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 4.0, 'NumberOfSymbolicFeatures': 1.0, 'cos...
hayes-roth
[ "hobby", "age", "educational_level", "marital_status" ]
[ false, false, false, false ]
1,531
2,939
predictive_accuracy
accuracy_score
satimage
**Author**: Ashwin Srinivasan, Department of Statistics and Data Modeling, University of Strathclyde **Source**: [UCI](https://archive.ics.uci.edu/ml/datasets/Statlog+(Landsat+Satellite)) - 1993 **Please cite**: [UCI](https://archive.ics.uci.edu/ml/citation_policy.html) The database consists of the multi-spectra...
{0: [0 - Aattr (numeric)], 1: [1 - Battr (numeric)], 2: [2 - Cattr (numeric)], 3: [3 - Dattr (numeric)], 4: [4 - Eattr (numeric)], 5: [5 - Fattr (numeric)], 6: [6 - A1attr (numeric)], 7: [7 - B2attr (numeric)], 8: [8 - C3attr (numeric)], 9: [9 - D4attr (numeric)], 10: [10 - E5attr (numeric)], 11: [11 - F6att...
{'MajorityClassSize': 1531.0, 'MaxNominalAttDistinctValues': 6.0, 'MinorityClassSize': 625.0, 'NumberOfClasses': 6.0, 'NumberOfFeatures': 37.0, 'NumberOfInstances': 6430.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 36.0, 'NumberOfSymbolicFeatures': 1.0,...
satimage
[ "Aattr", "Battr", "Cattr", "Dattr", "Eattr", "Fattr", "A1attr", "B2attr", "C3attr", "D4attr", "E5attr", "F6attr", "A7attr", "B8attr", "C9attr", "D10attr", "E11attr", "F12attr", "A13attr", "B14attr", "C15attr", "D16attr", "E17attr", "F18attr", "A19attr", "B20attr", ...
[ false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, f...
1,532
3,496
predictive_accuracy
accuracy_score
SPECTF
**Author**: Krzysztof J. Cios","Lukasz A. **Source**: [original](https://archive.ics.uci.edu/ml/datasets/SPECTF+Heart) - **Please cite**: SPECTF heart data This is a merged version of the separate train and test set which are usually distributed. On OpenML this train-test split can be found as one of the poss...
{0: [0 - OVERALL_DIAGNOSIS (nominal)], 1: [1 - F1R (numeric)], 2: [2 - F1S (numeric)], 3: [3 - F2R (numeric)], 4: [4 - F2S (numeric)], 5: [5 - F3R (numeric)], 6: [6 - F3S (numeric)], 7: [7 - F4R (numeric)], 8: [8 - F4S (numeric)], 9: [9 - F5R (numeric)], 10: [10 - F5S (numeric)], 11: [11 - F6R (numeric)], 1...
{'MajorityClassSize': 254.0, 'MaxNominalAttDistinctValues': 2.0, 'MinorityClassSize': 95.0, 'NumberOfClasses': 2.0, 'NumberOfFeatures': 45.0, 'NumberOfInstances': 349.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 44.0, 'NumberOfSymbolicFeatures': 1.0, '...
SPECTF
[ "F1R", "F1S", "F2R", "F2S", "F3R", "F3S", "F4R", "F4S", "F5R", "F5S", "F6R", "F6S", "F7R", "F7S", "F8R", "F8S", "F9R", "F9S", "F10R", "F10S", "F11R", "F11S", "F12R", "F12S", "F13R", "F13S", "F14R", "F14S", "F15R", "F15S", "F16R", "F16S", "F17R", "F17...
[ false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, f...
1,533
3,500
predictive_accuracy
accuracy_score
squash-unstored
**Author**: Winna Harvey **Source**: [original](http://www.cs.waikato.ac.nz/ml/weka/datasets.html) - **Please cite**: Squash Harvest Unstored Data source: Winna Harvey Crop and Food Research, Christchurch, New Zealand The purpose of the research was to determine the changes taking place in squash fruit durin...
{0: [0 - site (nominal)], 1: [1 - daf (nominal)], 2: [2 - fruit (nominal)], 3: [3 - weight (numeric)], 4: [4 - pene (numeric)], 5: [5 - solids (numeric)], 6: [6 - brix (numeric)], 7: [7 - a* (numeric)], 8: [8 - egdd (numeric)], 9: [9 - fgdd (numeric)], 10: [10 - groundspot_a* (numeric)], 11: [11 - glucose (n...
{'MajorityClassSize': 24.0, 'MaxNominalAttDistinctValues': 22.0, 'MinorityClassSize': 4.0, 'NumberOfClasses': 3.0, 'NumberOfFeatures': 24.0, 'NumberOfInstances': 52.0, 'NumberOfInstancesWithMissingValues': 9.0, 'NumberOfMissingValues': 39.0, 'NumberOfNumericFeatures': 20.0, 'NumberOfSymbolicFeatures': 4.0, 'c...
squash-unstored
[ "site", "daf", "fruit", "weight", "pene", "solids", "brix", "a*", "egdd", "fgdd", "groundspot_a*", "glucose", "fructose", "sucrose", "total", "glucose+fructose", "starch", "sweetness", "flavour", "dry/moist", "fibre", "heat_input_emerg", "heat_input_flower" ]
[ true, true, true, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false ]
1,534
3,025
predictive_accuracy
accuracy_score
hypothyroid
**Author**: **Source**: Unknown - **Please cite**: ; ; Thyroid disease records supplied by the Garavan Institute and J. Ross ; Quinlan, New South Wales Institute, Syndney, Australia. ; ; 1987. ; hypothyroid, primary hypothyroid, compensated hypothyroid, secondary hypothyroid, negative. | classes ...
{0: [0 - age (numeric)], 1: [1 - sex (nominal)], 2: [2 - on_thyroxine (nominal)], 3: [3 - query_on_thyroxine (nominal)], 4: [4 - on_antithyroid_medication (nominal)], 5: [5 - sick (nominal)], 6: [6 - pregnant (nominal)], 7: [7 - thyroid_surgery (nominal)], 8: [8 - I131_treatment (nominal)], 9: [9 - query_hypot...
{'MajorityClassSize': 3481.0, 'MaxNominalAttDistinctValues': 5.0, 'MinorityClassSize': 2.0, 'NumberOfClasses': 4.0, 'NumberOfFeatures': 30.0, 'NumberOfInstances': 3772.0, 'NumberOfInstancesWithMissingValues': 3772.0, 'NumberOfMissingValues': 6064.0, 'NumberOfNumericFeatures': 7.0, 'NumberOfSymbolicFeatures': 2...
hypothyroid
[ "age", "sex", "on_thyroxine", "query_on_thyroxine", "on_antithyroid_medication", "sick", "pregnant", "thyroid_surgery", "I131_treatment", "query_hypothyroid", "query_hyperthyroid", "lithium", "goitre", "tumor", "hypopituitary", "psych", "TSH_measured", "TSH", "T3_measured", "T3...
[ false, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, false, true, false, true, false, true, false, true, false, true, false, true ]
1,535
3,498
predictive_accuracy
accuracy_score
pasture
**Author**: Dave Barker **Source**: [original](http://www.cs.waikato.ac.nz/ml/weka/datasets.html) - **Please cite**: Pasture Production Data source: Dave Barker AgResearch Grasslands, Palmerston North, New Zealand The objective was to predict pasture production from a variety of biophysical factors. Vegeta...
{0: [0 - fertiliser (nominal)], 1: [1 - slope (numeric)], 2: [2 - aspect-dev-NW (numeric)], 3: [3 - OlsenP (numeric)], 4: [4 - MinN (numeric)], 5: [5 - TS (numeric)], 6: [6 - Ca-Mg (numeric)], 7: [7 - LOM (numeric)], 8: [8 - NFIX-mean (numeric)], 9: [9 - Eworms-main-3 (numeric)], 10: [10 - Eworms-No-species (...
{'MajorityClassSize': 12.0, 'MaxNominalAttDistinctValues': 4.0, 'MinorityClassSize': 12.0, 'NumberOfClasses': 3.0, 'NumberOfFeatures': 23.0, 'NumberOfInstances': 36.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 21.0, 'NumberOfSymbolicFeatures': 2.0, 'co...
pasture
[ "fertiliser", "slope", "aspect-dev-NW", "OlsenP", "MinN", "TS", "Ca-Mg", "LOM", "NFIX-mean", "Eworms-main-3", "Eworms-No-species", "KUnSat", "OM", "Air-Perm", "Porosity", "HFRG-pct-mean", "legume-yield", "OSPP-pct-mean", "Jan-Mar-mean-TDR", "Annual-Mean-Runoff", "root-surface...
[ true, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false ]
1,536
359,939
root_mean_squared_error
root_mean_squared_error
topo_2_1
**Author**: **Source**: Unknown - Date unknown **Please cite**: This is one of 41 drug design datasets. The datasets with 1143 features are formed using Adriana.Code software (www.molecular-networks.com/software/adrianacode). The molecules and outputs are taken from the original studies (see below). The other...
{0: [0 - oz1 (numeric)], 1: [1 - oz2 (numeric)], 2: [2 - oz3 (numeric)], 3: [3 - oz4 (numeric)], 4: [4 - oz5 (numeric)], 5: [5 - oz6 (numeric)], 6: [6 - oz7 (numeric)], 7: [7 - oz8 (numeric)], 8: [8 - oz9 (numeric)], 9: [9 - oz10 (numeric)], 10: [10 - oz11 (numeric)], 11: [11 - oz12 (numeric)], 12: [12 - oz...
{'MajorityClassSize': nan, 'MaxNominalAttDistinctValues': nan, 'MinorityClassSize': nan, 'NumberOfClasses': 0.0, 'NumberOfFeatures': 267.0, 'NumberOfInstances': 8885.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 267.0, 'NumberOfSymbolicFeatures': 0.0, '...
topo_2_1
[ "oz1", "oz2", "oz3", "oz4", "oz5", "oz6", "oz7", "oz8", "oz9", "oz10", "oz11", "oz12", "oz13", "oz14", "oz15", "oz16", "oz17", "oz18", "oz19", "oz20", "oz21", "oz22", "oz23", "oz24", "oz25", "oz26", "oz27", "oz28", "oz29", "oz30", "oz31", "oz32", "oz33...
[ false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, f...
1,537
3,044
predictive_accuracy
accuracy_score
hypothyroid
**Author**: **Source**: Unknown - **Please cite**: ; ; Thyroid disease records supplied by the Garavan Institute and J. Ross ; Quinlan, New South Wales Institute, Syndney, Australia. ; ; 1987. ; hypothyroid, primary hypothyroid, compensated hypothyroid, secondary hypothyroid, negative. | classes ...
{0: [0 - age (numeric)], 1: [1 - sex (nominal)], 2: [2 - on_thyroxine (nominal)], 3: [3 - query_on_thyroxine (nominal)], 4: [4 - on_antithyroid_medication (nominal)], 5: [5 - sick (nominal)], 6: [6 - pregnant (nominal)], 7: [7 - thyroid_surgery (nominal)], 8: [8 - I131_treatment (nominal)], 9: [9 - query_hypot...
{'MajorityClassSize': 3481.0, 'MaxNominalAttDistinctValues': 5.0, 'MinorityClassSize': 2.0, 'NumberOfClasses': 4.0, 'NumberOfFeatures': 30.0, 'NumberOfInstances': 3772.0, 'NumberOfInstancesWithMissingValues': 3772.0, 'NumberOfMissingValues': 6064.0, 'NumberOfNumericFeatures': 7.0, 'NumberOfSymbolicFeatures': 2...
hypothyroid
[ "age", "sex", "on_thyroxine", "query_on_thyroxine", "on_antithyroid_medication", "sick", "pregnant", "thyroid_surgery", "I131_treatment", "query_hypothyroid", "query_hyperthyroid", "lithium", "goitre", "tumor", "hypopituitary", "psych", "TSH_measured", "TSH", "T3_measured", "T3...
[ false, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, false, true, false, true, false, true, false, true, false, true, false, true ]
1,538
3,043
predictive_accuracy
accuracy_score
sick
**Author**: Ross Quinlan **Source**: [UCI](http://archive.ics.uci.edu/ml/datasets/thyroid+disease) **Please cite**: Thyroid disease records supplied by the Garavan Institute and J. Ross Quinlan, New South Wales Institute, Syndney, Australia. 1987. Attribute information: ``` sick, negative. | classes age: co...
{0: [0 - age (numeric)], 1: [1 - sex (nominal)], 2: [2 - on_thyroxine (nominal)], 3: [3 - query_on_thyroxine (nominal)], 4: [4 - on_antithyroid_medication (nominal)], 5: [5 - sick (nominal)], 6: [6 - pregnant (nominal)], 7: [7 - thyroid_surgery (nominal)], 8: [8 - I131_treatment (nominal)], 9: [9 - query_hypot...
{'MajorityClassSize': 3541.0, 'MaxNominalAttDistinctValues': 5.0, 'MinorityClassSize': 231.0, 'NumberOfClasses': 2.0, 'NumberOfFeatures': 30.0, 'NumberOfInstances': 3772.0, 'NumberOfInstancesWithMissingValues': 3772.0, 'NumberOfMissingValues': 6064.0, 'NumberOfNumericFeatures': 7.0, 'NumberOfSymbolicFeatures':...
sick
[ "age", "sex", "on_thyroxine", "query_on_thyroxine", "on_antithyroid_medication", "sick", "pregnant", "thyroid_surgery", "I131_treatment", "query_hypothyroid", "query_hyperthyroid", "lithium", "goitre", "tumor", "hypopituitary", "psych", "TSH_measured", "TSH", "T3_measured", "T3...
[ false, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, false, true, false, true, false, true, false, true, false, true, false, true ]
1,539
3,497
predictive_accuracy
accuracy_score
grub-damage
**Author**: R. J. Townsend **Source**: [original](http://www.cs.waikato.ac.nz/ml/weka/datasets.html) - **Please cite**: Grass Grubs and Damage Ranking Data source: R. J. Townsend AgResearch, Lincoln, New Zealand Grass grubs are one of the major insect pests of pasture in Canterbury and can cause severe pa...
{0: [0 - year_zone (nominal)], 1: [1 - year (nominal)], 2: [2 - strip (numeric)], 3: [3 - pdk (numeric)], 4: [4 - damage_rankRJT (nominal)], 5: [5 - damage_rankALL (nominal)], 6: [6 - dry_or_irr (nominal)], 7: [7 - zone (nominal)], 8: [8 - GG_new (nominal)]}
{'MajorityClassSize': 49.0, 'MaxNominalAttDistinctValues': 21.0, 'MinorityClassSize': 19.0, 'NumberOfClasses': 4.0, 'NumberOfFeatures': 9.0, 'NumberOfInstances': 155.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 2.0, 'NumberOfSymbolicFeatures': 7.0, 'co...
grub-damage
[ "year_zone", "year", "strip", "pdk", "damage_rankRJT", "damage_rankALL", "dry_or_irr", "zone" ]
[ true, true, false, false, true, true, true, true ]
1,540
3,024
predictive_accuracy
accuracy_score
sick
**Author**: Ross Quinlan **Source**: [UCI](http://archive.ics.uci.edu/ml/datasets/thyroid+disease) **Please cite**: Thyroid disease records supplied by the Garavan Institute and J. Ross Quinlan, New South Wales Institute, Syndney, Australia. 1987. Attribute information: ``` sick, negative. | classes age: co...
{0: [0 - age (numeric)], 1: [1 - sex (nominal)], 2: [2 - on_thyroxine (nominal)], 3: [3 - query_on_thyroxine (nominal)], 4: [4 - on_antithyroid_medication (nominal)], 5: [5 - sick (nominal)], 6: [6 - pregnant (nominal)], 7: [7 - thyroid_surgery (nominal)], 8: [8 - I131_treatment (nominal)], 9: [9 - query_hypot...
{'MajorityClassSize': 3541.0, 'MaxNominalAttDistinctValues': 5.0, 'MinorityClassSize': 231.0, 'NumberOfClasses': 2.0, 'NumberOfFeatures': 30.0, 'NumberOfInstances': 3772.0, 'NumberOfInstancesWithMissingValues': 3772.0, 'NumberOfMissingValues': 6064.0, 'NumberOfNumericFeatures': 7.0, 'NumberOfSymbolicFeatures':...
sick
[ "age", "sex", "on_thyroxine", "query_on_thyroxine", "on_antithyroid_medication", "sick", "pregnant", "thyroid_surgery", "I131_treatment", "query_hypothyroid", "query_hyperthyroid", "lithium", "goitre", "tumor", "hypopituitary", "psych", "TSH_measured", "TSH", "T3_measured", "T3...
[ false, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, false, true, false, true, false, true, false, true, false, true, false, true ]
1,541
3,538
predictive_accuracy
accuracy_score
analcatdata_boxing2
**Author**: **Source**: Unknown - Date unknown **Please cite**: analcatdata A collection of data sets used in the book "Analyzing Categorical Data," by Jeffrey S. Simonoff, Springer-Verlag, New York, 2003. The submission consists of a zip file containing two versions of each of 84 data sets, plus this READM...
{0: [0 - Judge (nominal)], 1: [1 - Official (nominal)], 2: [2 - Round (nominal)], 3: [3 - Winner (nominal)]}
{'MajorityClassSize': 71.0, 'MaxNominalAttDistinctValues': 12.0, 'MinorityClassSize': 61.0, 'NumberOfClasses': 2.0, 'NumberOfFeatures': 4.0, 'NumberOfInstances': 132.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 0.0, 'NumberOfSymbolicFeatures': 4.0, 'co...
analcatdata_boxing2
[ "Judge", "Official", "Round" ]
[ true, true, true ]
1,542
3,539
predictive_accuracy
accuracy_score
prnn_crabs
**Author**: **Source**: Unknown - Date unknown **Please cite**: Datasets for `Pattern Recognition and Neural Networks' by B.D. Ripley ===================================================================== Cambridge University Press (1996) ISBN 0-521-46086-7 The background to the datasets is described in sec...
{0: [0 - sp (nominal)], 1: [1 - sex (nominal)], 2: [2 - index (numeric)], 3: [3 - FL (numeric)], 4: [4 - RW (numeric)], 5: [5 - CL (numeric)], 6: [6 - CW (numeric)], 7: [7 - BD (numeric)]}
{'MajorityClassSize': 100.0, 'MaxNominalAttDistinctValues': 2.0, 'MinorityClassSize': 100.0, 'NumberOfClasses': 2.0, 'NumberOfFeatures': 8.0, 'NumberOfInstances': 200.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 6.0, 'NumberOfSymbolicFeatures': 2.0, 'c...
prnn_crabs
[ "sex", "index", "FL", "RW", "CL", "CW", "BD" ]
[ true, false, false, false, false, false, false ]
1,543
3,540
predictive_accuracy
accuracy_score
analcatdata_boxing1
**Author**: **Source**: Unknown - Date unknown **Please cite**: analcatdata A collection of data sets used in the book "Analyzing Categorical Data," by Jeffrey S. Simonoff, Springer-Verlag, New York, 2003. The submission consists of a zip file containing two versions of each of 84 data sets, plus this READM...
{0: [0 - Judge (nominal)], 1: [1 - Official (nominal)], 2: [2 - Round (nominal)], 3: [3 - Winner (nominal)]}
{'MajorityClassSize': 78.0, 'MaxNominalAttDistinctValues': 12.0, 'MinorityClassSize': 42.0, 'NumberOfClasses': 2.0, 'NumberOfFeatures': 4.0, 'NumberOfInstances': 120.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 0.0, 'NumberOfSymbolicFeatures': 4.0, 'co...
analcatdata_boxing1
[ "Judge", "Official", "Round" ]
[ true, true, true ]
1,544
3,542
predictive_accuracy
accuracy_score
analcatdata_lawsuit
**Author**: **Source**: Unknown - Date unknown **Please cite**: analcatdata A collection of data sets used in the book "Analyzing Categorical Data," by Jeffrey S. Simonoff, Springer-Verlag, New York, 2003. The submission consists of a zip file containing two versions of each of 84 data sets, plus this READM...
{0: [0 - Length.of.service (numeric)], 1: [1 - CAP (numeric)], 2: [2 - PA.normalized (numeric)], 3: [3 - Minority (nominal)], 4: [4 - Laid.off (nominal)]}
{'MajorityClassSize': 245.0, 'MaxNominalAttDistinctValues': 2.0, 'MinorityClassSize': 19.0, 'NumberOfClasses': 2.0, 'NumberOfFeatures': 5.0, 'NumberOfInstances': 264.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 3.0, 'NumberOfSymbolicFeatures': 2.0, 'co...
analcatdata_lawsuit
[ "Length.of.service", "CAP", "PA.normalized", "Minority" ]
[ false, false, false, true ]
1,546
3,544
predictive_accuracy
accuracy_score
analcatdata_broadwaymult
**Author**: **Source**: Unknown - Date unknown **Please cite**: analcatdata A collection of data sets used in the book "Analyzing Categorical Data," by Jeffrey S. Simonoff, Springer-Verlag, New York, 2003. The submission consists of a zip file containing two versions of each of 84 data sets, plus this READM...
{0: [0 - Show (nominal)], 1: [1 - Type (nominal)], 2: [2 - Revival (nominal)], 3: [3 - NYT_rating (numeric)], 4: [4 - DN_rating (numeric)], 5: [5 - Week_1_attendance (numeric)], 6: [6 - Award (nominal)], 7: [7 - Count (nominal)]}
{'MajorityClassSize': 118.0, 'MaxNominalAttDistinctValues': 95.0, 'MinorityClassSize': 21.0, 'NumberOfClasses': 7.0, 'NumberOfFeatures': 8.0, 'NumberOfInstances': 285.0, 'NumberOfInstancesWithMissingValues': 18.0, 'NumberOfMissingValues': 27.0, 'NumberOfNumericFeatures': 3.0, 'NumberOfSymbolicFeatures': 5.0, ...
analcatdata_broadwaymult
[ "Show", "Type", "Revival", "NYT_rating", "DN_rating", "Week_1_attendance", "Award" ]
[ true, true, true, false, false, false, true ]
1,547
3,537
predictive_accuracy
accuracy_score
analcatdata_broadway
**Author**: **Source**: Unknown - Date unknown **Please cite**: analcatdata A collection of data sets used in the book "Analyzing Categorical Data," by Jeffrey S. Simonoff, Springer-Verlag, New York, 2003. The submission consists of a zip file containing two versions of each of 84 data sets, plus this READM...
{0: [0 - Show (nominal)], 1: [1 - Type (nominal)], 2: [2 - Revival (nominal)], 3: [3 - NYT_rating (numeric)], 4: [4 - DN_rating (numeric)], 5: [5 - Tony_awards (nominal)], 6: [6 - Tony_nominations (nominal)], 7: [7 - Week_1_attendance (numeric)], 8: [8 - Show_run (nominal)], 9: [9 - Show_run_code (nominal)]}
{'MajorityClassSize': 68.0, 'MaxNominalAttDistinctValues': 7.0, 'MinorityClassSize': 1.0, 'NumberOfClasses': 5.0, 'NumberOfFeatures': 8.0, 'NumberOfInstances': 95.0, 'NumberOfInstancesWithMissingValues': 6.0, 'NumberOfMissingValues': 9.0, 'NumberOfNumericFeatures': 3.0, 'NumberOfSymbolicFeatures': 5.0, 'cost_...
analcatdata_broadway
[ "Type", "Revival", "NYT_rating", "DN_rating", "Tony_awards", "Tony_nominations", "Week_1_attendance" ]
[ true, true, false, false, true, true, false ]
1,548
3,545
predictive_accuracy
accuracy_score
analcatdata_bondrate
**Author**: **Source**: Unknown - Date unknown **Please cite**: analcatdata A collection of data sets used in the book "Analyzing Categorical Data," by Jeffrey S. Simonoff, Springer-Verlag, New York, 2003. The submission consists of a zip file containing two versions of each of 84 data sets, plus this READM...
{0: [0 - City (nominal)], 1: [1 - Population (numeric)], 2: [2 - Per_capita_income (numeric)], 3: [3 - Household_income (numeric)], 4: [4 - Discretionary_income (numeric)], 5: [5 - Publics_in_top_10 (nominal)], 6: [6 - Nonprofits_in_top_10 (nominal)], 7: [7 - For_profits_in_top_10 (nominal)], 8: [8 - Utilities_...
{'MajorityClassSize': 33.0, 'MaxNominalAttDistinctValues': 10.0, 'MinorityClassSize': 1.0, 'NumberOfClasses': 5.0, 'NumberOfFeatures': 11.0, 'NumberOfInstances': 57.0, 'NumberOfInstancesWithMissingValues': 1.0, 'NumberOfMissingValues': 1.0, 'NumberOfNumericFeatures': 4.0, 'NumberOfSymbolicFeatures': 7.0, 'cos...
analcatdata_bondrate
[ "Population", "Per_capita_income", "Household_income", "Discretionary_income", "Publics_in_top_10", "Nonprofits_in_top_10", "For_profits_in_top_10", "Utilities_in_top_10", "Region", "State_capital" ]
[ false, false, false, false, true, true, true, true, true, true ]
1,549
3,548
predictive_accuracy
accuracy_score
prnn_cushings
**Author**: **Source**: Unknown - Date unknown **Please cite**: Datasets for `Pattern Recognition and Neural Networks' by B.D. Ripley ===================================================================== Cambridge University Press (1996) ISBN 0-521-46086-7 The background to the datasets is described in sec...
{0: [0 - Label (nominal)], 1: [1 - Tetrahydrocortisone (numeric)], 2: [2 - Pregnanetriol (numeric)], 3: [3 - Type (nominal)]}
{'MajorityClassSize': 12.0, 'MaxNominalAttDistinctValues': 4.0, 'MinorityClassSize': 2.0, 'NumberOfClasses': 4.0, 'NumberOfFeatures': 3.0, 'NumberOfInstances': 27.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 2.0, 'NumberOfSymbolicFeatures': 1.0, 'cost_...
prnn_cushings
[ "Tetrahydrocortisone", "Pregnanetriol" ]
[ false, false ]
1,551
3,562
predictive_accuracy
accuracy_score
lupus
**Author**: **Source**: Unknown - Date unknown **Please cite**: 87 persons with lupus nephritis. Followed up 15+ years. 35 deaths. Var = duration of disease. Over 40 baseline variables avaiable from authors. Description : For description of this data set arising from 87 persons with lupus nephritis followed fo...
{0: [0 - TIME (numeric)], 1: [1 - STATUS (nominal)], 2: [2 - DURATION (numeric)], 3: [3 - LOG(1+DURATION) (numeric)]}
{'MajorityClassSize': 52.0, 'MaxNominalAttDistinctValues': 2.0, 'MinorityClassSize': 35.0, 'NumberOfClasses': 2.0, 'NumberOfFeatures': 4.0, 'NumberOfInstances': 87.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 3.0, 'NumberOfSymbolicFeatures': 1.0, 'cost...
lupus
[ "TIME", "DURATION", "LOG(1+DURATION)" ]
[ false, false, false ]
1,553
3,550
predictive_accuracy
accuracy_score
analcatdata_asbestos
**Author**: **Source**: Unknown - Date unknown **Please cite**: analcatdata A collection of data sets used in the book "Analyzing Categorical Data," by Jeffrey S. Simonoff, Springer-Verlag, New York, 2003. The submission consists of a zip file containing two versions of each of 84 data sets, plus this READM...
{0: [0 - Task (nominal)], 1: [1 - Ventilation (nominal)], 2: [2 - Duration (numeric)], 3: [3 - Exposure (nominal)]}
{'MajorityClassSize': 46.0, 'MaxNominalAttDistinctValues': 3.0, 'MinorityClassSize': 37.0, 'NumberOfClasses': 2.0, 'NumberOfFeatures': 4.0, 'NumberOfInstances': 83.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 1.0, 'NumberOfSymbolicFeatures': 3.0, 'cost...
analcatdata_asbestos
[ "Ventilation", "Duration", "Exposure" ]
[ true, false, true ]
1,554
3,555
predictive_accuracy
accuracy_score
prnn_synth
**Author**: B.D. Ripley **Source**: Unknown - Date unknown **Please cite**: Dataset from `Pattern Recognition and Neural Networks' by B.D. Ripley. Cambridge University Press (1996) ISBN 0-521-46086-7. The background to the datasets is described in section 1.4; this file relates the computer-readable files to ...
{0: [0 - xs (numeric)], 1: [1 - ys (numeric)], 2: [2 - yc (nominal)]}
{'MajorityClassSize': 125.0, 'MaxNominalAttDistinctValues': 2.0, 'MinorityClassSize': 125.0, 'NumberOfClasses': 2.0, 'NumberOfFeatures': 3.0, 'NumberOfInstances': 250.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 2.0, 'NumberOfSymbolicFeatures': 1.0, 'c...
prnn_synth
[ "xs", "ys" ]
[ false, false ]
1,555
3,554
predictive_accuracy
accuracy_score
backache
**Author**: **Source**: Unknown - Date unknown **Please cite**: Data file: This data from "Problem-Solving" on "backache in pregnancy" is in somewhat different format from that listed in the book. Each integer is preceded by a space. This makes it easier to read. Each line is split in two separated by an amper...
{0: [0 - id (numeric)], 1: [1 - col_2 (nominal)], 2: [2 - col_3 (nominal)], 3: [3 - col_4 (numeric)], 4: [4 - col_5 (numeric)], 5: [5 - col_6 (numeric)], 6: [6 - col_7 (numeric)], 7: [7 - col_8 (numeric)], 8: [8 - col_9 (nominal)], 9: [9 - col_10 (nominal)], 10: [10 - col_11 (nominal)], 11: [11 - col_12 (nom...
{'MajorityClassSize': 155.0, 'MaxNominalAttDistinctValues': 10.0, 'MinorityClassSize': 25.0, 'NumberOfClasses': 2.0, 'NumberOfFeatures': 32.0, 'NumberOfInstances': 180.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 5.0, 'NumberOfSymbolicFeatures': 27.0, ...
backache
[ "col_2", "col_3", "col_4", "col_5", "col_6", "col_7", "col_8", "col_9", "col_10", "col_11", "col_12", "col_13", "col_14", "col_15", "col_16", "col_17", "col_18", "col_19", "col_20", "col_21", "col_22", "col_23", "col_24", "col_25", "col_26", "col_27", "col_28", ...
[ true, true, false, false, false, false, false, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true ]
1,556
3,547
predictive_accuracy
accuracy_score
cars
**Author**: **Source**: Unknown - Date unknown **Please cite**: The Committee on Statistical Graphics of the American Statistical Association (ASA) invites you to participate in its Second (1983) Exposition of Statistical Graphics Technology. The purposes of the Exposition are (l) to provide a forum in which u...
{0: [0 - name (nominal)], 1: [1 - mpg (numeric)], 2: [2 - cylinders (nominal)], 3: [3 - displacement (numeric)], 4: [4 - horsepower (numeric)], 5: [5 - weight (numeric)], 6: [6 - acceleration (numeric)], 7: [7 - model.year (numeric)], 8: [8 - origin (nominal)]}
{'MajorityClassSize': 254.0, 'MaxNominalAttDistinctValues': 5.0, 'MinorityClassSize': 73.0, 'NumberOfClasses': 3.0, 'NumberOfFeatures': 8.0, 'NumberOfInstances': 406.0, 'NumberOfInstancesWithMissingValues': 14.0, 'NumberOfMissingValues': 14.0, 'NumberOfNumericFeatures': 6.0, 'NumberOfSymbolicFeatures': 2.0, '...
cars
[ "mpg", "cylinders", "displacement", "horsepower", "weight", "acceleration", "model.year" ]
[ false, true, false, false, false, false, false ]
1,557
3,552
predictive_accuracy
accuracy_score
analcatdata_creditscore
**Author**: **Source**: Unknown - Date unknown **Please cite**: analcatdata A collection of data sets used in the book "Analyzing Categorical Data," by Jeffrey S. Simonoff, Springer-Verlag, New York, 2003. The submission consists of a zip file containing two versions of each of 84 data sets, plus this READM...
{0: [0 - Age (numeric)], 1: [1 - Income.per.dependent (numeric)], 2: [2 - Monthly.credit.card.exp (numeric)], 3: [3 - Own.home (nominal)], 4: [4 - Self.employed (nominal)], 5: [5 - Derogatory.reports (nominal)], 6: [6 - Application.accepted (nominal)]}
{'MajorityClassSize': 73.0, 'MaxNominalAttDistinctValues': 6.0, 'MinorityClassSize': 27.0, 'NumberOfClasses': 2.0, 'NumberOfFeatures': 7.0, 'NumberOfInstances': 100.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 3.0, 'NumberOfSymbolicFeatures': 4.0, 'cos...
analcatdata_creditscore
[ "Age", "Income.per.dependent", "Monthly.credit.card.exp", "Own.home", "Self.employed", "Derogatory.reports" ]
[ false, false, false, true, true, true ]
1,558
3,559
predictive_accuracy
accuracy_score
confidence
**Author**: **Source**: Unknown - Date unknown **Please cite**: CODING: ITEM 1 = BUSINESS CONDIDIONS 6 MONTHS FROM NOW (CONFERENCE BOARD) ITEM 2 = JOBS 6 MONTHS FROM NOW (CONFERENCE BOARD) ITEM 3 = FAMILY INCOME 6 MONTHS FROM NOW (CONFERENCE BOARD) ITEM 4 = BUSINESS CONDITIONS A YEAR FROM NOW (MICHIGAN) IT...
{0: [0 - ITEM (nominal)], 1: [1 - P (numeric)], 2: [2 - N (numeric)], 3: [3 - O (numeric)]}
{'MajorityClassSize': 12.0, 'MaxNominalAttDistinctValues': 6.0, 'MinorityClassSize': 12.0, 'NumberOfClasses': 6.0, 'NumberOfFeatures': 4.0, 'NumberOfInstances': 72.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 3.0, 'NumberOfSymbolicFeatures': 1.0, 'cost...
confidence
[ "P", "N", "O" ]
[ false, false, false ]
1,559
3,508
predictive_accuracy
accuracy_score
UNIX_user_data
**Author**: Terran Lane (terran@ecn.purdue.edu) **Source**: [UCI](https://archive.ics.uci.edu/ml/datasets/UNIX+User+Data) - Date unknown **Please cite**: This file contains 9 sets of sanitized user data drawn from the command histories of 8 UNIX computer users at Purdue over the course of up to 2 years (USER0 ...
{0: [0 - history (numeric)], 1: [1 - session (string)], 2: [2 - user (nominal)]}
{'MajorityClassSize': 2425.0, 'MaxNominalAttDistinctValues': 9.0, 'MinorityClassSize': 484.0, 'NumberOfClasses': 9.0, 'NumberOfFeatures': 3.0, 'NumberOfInstances': 9100.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 1.0, 'NumberOfSymbolicFeatures': 1.0, ...
UNIX_user_data
[ "history", "session" ]
[ false, false ]
1,560
3,557
predictive_accuracy
accuracy_score
schizo
**Author**: **Source**: Unknown - Date unknown **Please cite**: Schizophrenic Eye-Tracking Data in Rubin and Wu (1997) Biometrics. Yingnian Wu (wu@hustat.harvard.edu) [14/Oct/97] Information about the dataset CLASSTYPE: nominal CLASSINDEX: last
{0: [0 - ID (numeric)], 1: [1 - target (nominal)], 2: [2 - gain_ratio_1 (numeric)], 3: [3 - gain_ratio_2 (numeric)], 4: [4 - gain_ratio_3 (numeric)], 5: [5 - gain_ratio_4 (numeric)], 6: [6 - gain_ratio_5 (numeric)], 7: [7 - gain_ratio_6 (numeric)], 8: [8 - gain_ratio_7 (numeric)], 9: [9 - gain_ratio_8 (numeric...
{'MajorityClassSize': 177.0, 'MaxNominalAttDistinctValues': 3.0, 'MinorityClassSize': 163.0, 'NumberOfClasses': 2.0, 'NumberOfFeatures': 15.0, 'NumberOfInstances': 340.0, 'NumberOfInstancesWithMissingValues': 228.0, 'NumberOfMissingValues': 834.0, 'NumberOfNumericFeatures': 12.0, 'NumberOfSymbolicFeatures': 3....
schizo
[ "ID", "target", "gain_ratio_1", "gain_ratio_2", "gain_ratio_3", "gain_ratio_4", "gain_ratio_5", "gain_ratio_6", "gain_ratio_7", "gain_ratio_8", "gain_ratio_9", "gain_ratio_10", "gain_ratio_11", "sex" ]
[ false, true, false, false, false, false, false, false, false, false, false, false, false, true ]
1,561
3,553
predictive_accuracy
accuracy_score
analcatdata_challenger
**Author**: **Source**: Unknown - Date unknown **Please cite**: analcatdata A collection of data sets used in the book "Analyzing Categorical Data," by Jeffrey S. Simonoff, Springer-Verlag, New York, 2003. The submission consists of a zip file containing two versions of each of 84 data sets, plus this READM...
{0: [0 - Date (nominal)], 1: [1 - Temperature (numeric)], 2: [2 - Pressure (nominal)], 3: [3 - Damaged (nominal)], 4: [4 - O-rings (nominal)], 5: [5 - Nozzle_joint (nominal)]}
{'MajorityClassSize': 16.0, 'MaxNominalAttDistinctValues': 3.0, 'MinorityClassSize': 2.0, 'NumberOfClasses': 3.0, 'NumberOfFeatures': 5.0, 'NumberOfInstances': 23.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 1.0, 'NumberOfSymbolicFeatures': 4.0, 'cost_...
analcatdata_challenger
[ "Temperature", "Pressure", "O-rings", "Nozzle_joint" ]
[ false, true, true, true ]
1,562
3,564
predictive_accuracy
accuracy_score
analcatdata_germangss
**Author**: **Source**: Unknown - Date unknown **Please cite**: analcatdata A collection of data sets used in the book "Analyzing Categorical Data," by Jeffrey S. Simonoff, Springer-Verlag, New York, 2003. The submission consists of a zip file containing two versions of each of 84 data sets, plus this READM...
{0: [0 - Political_system (nominal)], 1: [1 - Age (nominal)], 2: [2 - Time_of_survey (nominal)], 3: [3 - Schooling (nominal)], 4: [4 - Region (nominal)], 5: [5 - Count (numeric)]}
{'MajorityClassSize': 100.0, 'MaxNominalAttDistinctValues': 5.0, 'MinorityClassSize': 100.0, 'NumberOfClasses': 4.0, 'NumberOfFeatures': 6.0, 'NumberOfInstances': 400.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 1.0, 'NumberOfSymbolicFeatures': 5.0, 'c...
analcatdata_germangss
[ "Age", "Time_of_survey", "Schooling", "Region", "Count" ]
[ true, true, true, true, false ]
1,563
3,580
predictive_accuracy
accuracy_score
fruitfly
**Author**: **Source**: Unknown - Date unknown **Please cite**: Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a lower target value as positive ('P') and all others...
{0: [0 - PARTNERS (nominal)], 1: [1 - TYPE (nominal)], 2: [2 - THORAX (numeric)], 3: [3 - SLEEP (numeric)], 4: [4 - binaryClass (nominal)]}
{'MajorityClassSize': 76.0, 'MaxNominalAttDistinctValues': 3.0, 'MinorityClassSize': 49.0, 'NumberOfClasses': 2.0, 'NumberOfFeatures': 5.0, 'NumberOfInstances': 125.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 2.0, 'NumberOfSymbolicFeatures': 3.0, 'cos...
fruitfly
[ "PARTNERS", "TYPE", "THORAX", "SLEEP" ]
[ true, true, false, false ]
1,564
3,558
predictive_accuracy
accuracy_score
analcatdata_japansolvent
**Author**: **Source**: Unknown - Date unknown **Please cite**: analcatdata A collection of data sets used in the book "Analyzing Categorical Data," by Jeffrey S. Simonoff, Springer-Verlag, New York, 2003. The submission consists of a zip file containing two versions of each of 84 data sets, plus this READM...
{0: [0 - Firm (nominal)], 1: [1 - Solvent (nominal)], 2: [2 - EBIT/TA (numeric)], 3: [3 - NI/TC (numeric)], 4: [4 - Sales/TA (numeric)], 5: [5 - EBIT/Sales (numeric)], 6: [6 - NI/Sales (numeric)], 7: [7 - WC/TA (numeric)], 8: [8 - Equity/TL (numeric)], 9: [9 - Equity/TA (numeric)]}
{'MajorityClassSize': 27.0, 'MaxNominalAttDistinctValues': 2.0, 'MinorityClassSize': 25.0, 'NumberOfClasses': 2.0, 'NumberOfFeatures': 9.0, 'NumberOfInstances': 52.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 8.0, 'NumberOfSymbolicFeatures': 1.0, 'cost...
analcatdata_japansolvent
[ "EBIT/TA", "NI/TC", "Sales/TA", "EBIT/Sales", "NI/Sales", "WC/TA", "Equity/TL", "Equity/TA" ]
[ false, false, false, false, false, false, false, false ]
1,565
3,546
predictive_accuracy
accuracy_score
analcatdata_halloffame
**Author**: **Source**: Unknown - Date unknown **Please cite**: analcatdata A collection of data sets used in the book "Analyzing Categorical Data," by Jeffrey S. Simonoff, Springer-Verlag, New York, 2003. The submission consists of a zip file containing two versions of each of 84 data sets, plus this READM...
{0: [0 - Player (nominal)], 1: [1 - Number_seasons (numeric)], 2: [2 - Games_played (numeric)], 3: [3 - At_bats (numeric)], 4: [4 - Runs (numeric)], 5: [5 - Hits (numeric)], 6: [6 - Doubles (numeric)], 7: [7 - Triples (numeric)], 8: [8 - Home_runs (numeric)], 9: [9 - RBIs (numeric)], 10: [10 - Walks (numeric)...
{'MajorityClassSize': 1215.0, 'MaxNominalAttDistinctValues': 7.0, 'MinorityClassSize': 57.0, 'NumberOfClasses': 3.0, 'NumberOfFeatures': 17.0, 'NumberOfInstances': 1340.0, 'NumberOfInstancesWithMissingValues': 20.0, 'NumberOfMissingValues': 20.0, 'NumberOfNumericFeatures': 15.0, 'NumberOfSymbolicFeatures': 2.0...
analcatdata_halloffame
[ "Number_seasons", "Games_played", "At_bats", "Runs", "Hits", "Doubles", "Triples", "Home_runs", "RBIs", "Walks", "Strikeouts", "Batting_average", "On_base_pct", "Slugging_pct", "Fielding_ave", "Position" ]
[ false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, true ]
1,566
3,551
predictive_accuracy
accuracy_score
analcatdata_reviewer
**Author**: **Source**: Unknown - Date unknown **Please cite**: analcatdata A collection of data sets used in the book "Analyzing Categorical Data," by Jeffrey S. Simonoff, Springer-Verlag, New York, 2003. The submission consists of a zip file containing two versions of each of 84 data sets, plus this READM...
{0: [0 - Film (nominal)], 1: [1 - Roger_Ebert (nominal)], 2: [2 - Jeffrey_Lyons (nominal)], 3: [3 - Michael_Medved (nominal)], 4: [4 - Rex_Reed (nominal)], 5: [5 - Gene_Shalit (nominal)], 6: [6 - Joel_Siegel (nominal)], 7: [7 - Gene_Siskel (nominal)], 8: [8 - Peter_Travers (nominal)]}
{'MajorityClassSize': 141.0, 'MaxNominalAttDistinctValues': 3.0, 'MinorityClassSize': 54.0, 'NumberOfClasses': 4.0, 'NumberOfFeatures': 8.0, 'NumberOfInstances': 379.0, 'NumberOfInstancesWithMissingValues': 365.0, 'NumberOfMissingValues': 1418.0, 'NumberOfNumericFeatures': 0.0, 'NumberOfSymbolicFeatures': 8.0,...
analcatdata_reviewer
[ "Jeffrey_Lyons", "Michael_Medved", "Rex_Reed", "Gene_Shalit", "Joel_Siegel", "Gene_Siskel", "Peter_Travers" ]
[ true, true, true, true, true, true, true ]
1,567
3,563
predictive_accuracy
accuracy_score
analcatdata_marketing
**Author**: **Source**: Unknown - Date unknown **Please cite**: analcatdata A collection of data sets used in the book "Analyzing Categorical Data," by Jeffrey S. Simonoff, Springer-Verlag, New York, 2003. The submission consists of a zip file containing two versions of each of 84 data sets, plus this READM...
{0: [0 - X1a (nominal)], 1: [1 - X1b (nominal)], 2: [2 - X1c (nominal)], 3: [3 - X1d (nominal)], 4: [4 - X1e (nominal)], 5: [5 - X1f (nominal)], 6: [6 - X1g (nominal)], 7: [7 - X1h (nominal)], 8: [8 - X1i (nominal)], 9: [9 - X1j (nominal)], 10: [10 - X1k (nominal)], 11: [11 - X1l (nominal)], 12: [12 - X1m (...
{'MajorityClassSize': 203.0, 'MaxNominalAttDistinctValues': 5.0, 'MinorityClassSize': 2.0, 'NumberOfClasses': 6.0, 'NumberOfFeatures': 33.0, 'NumberOfInstances': 364.0, 'NumberOfInstancesWithMissingValues': 53.0, 'NumberOfMissingValues': 101.0, 'NumberOfNumericFeatures': 0.0, 'NumberOfSymbolicFeatures': 33.0, ...
analcatdata_marketing
[ "X1b", "X1c", "X1d", "X1e", "X1f", "X1g", "X1h", "X1i", "X1j", "X1k", "X1l", "X1m", "X1n", "X1o", "X2a", "X2b", "X2c", "X2d", "X2e", "X2f", "X2g", "X2h", "X2i", "X2j", "X2k", "X2l", "X2m", "X3a", "X3b", "X3c", "X5", "X9" ]
[ true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true ]
1,568
3,565
predictive_accuracy
accuracy_score
analcatdata_bankruptcy
**Author**: **Source**: Unknown - Date unknown **Please cite**: analcatdata A collection of data sets used in the book "Analyzing Categorical Data," by Jeffrey S. Simonoff, Springer-Verlag, New York, 2003. The submission consists of a zip file containing two versions of each of 84 data sets, plus this READM...
{0: [0 - Company (nominal)], 1: [1 - WC/TA (numeric)], 2: [2 - RE/TA (numeric)], 3: [3 - EBIT/TA (numeric)], 4: [4 - S/TA (numeric)], 5: [5 - BVE/BVL (numeric)], 6: [6 - Bankrupt (nominal)]}
{'MajorityClassSize': 25.0, 'MaxNominalAttDistinctValues': 2.0, 'MinorityClassSize': 25.0, 'NumberOfClasses': 2.0, 'NumberOfFeatures': 6.0, 'NumberOfInstances': 50.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 5.0, 'NumberOfSymbolicFeatures': 1.0, 'cost...
analcatdata_bankruptcy
[ "WC/TA", "RE/TA", "EBIT/TA", "S/TA", "BVE/BVL" ]
[ false, false, false, false, false ]
1,569
3,570
predictive_accuracy
accuracy_score
biomed
**Author**: **Source**: Unknown - Date unknown **Please cite**: February 23, 1982 The 1982 annual meetings of the American Statistical Association (ASA) will be held August 16-19, 1982 in Cincinnati. At that meeting, the ASA Committee on Statistical Graphics plans to sponsor an "Exposition of Statistical Gra...
{0: [0 - Observation_number (nominal)], 1: [1 - Hospital_identification_number_for_blood_sample (numeric)], 2: [2 - Age_of_patient (numeric)], 3: [3 - Date_that_blood_sample_was_taken (numeric)], 4: [4 - ml (numeric)], 5: [5 - m2 (numeric)], 6: [6 - m3 (numeric)], 7: [7 - m4 (numeric)], 8: [8 - class (nominal)]...
{'MajorityClassSize': 134.0, 'MaxNominalAttDistinctValues': 7.0, 'MinorityClassSize': 75.0, 'NumberOfClasses': 2.0, 'NumberOfFeatures': 9.0, 'NumberOfInstances': 209.0, 'NumberOfInstancesWithMissingValues': 15.0, 'NumberOfMissingValues': 15.0, 'NumberOfNumericFeatures': 7.0, 'NumberOfSymbolicFeatures': 2.0, '...
biomed
[ "Observation_number", "Hospital_identification_number_for_blood_sample", "Age_of_patient", "Date_that_blood_sample_was_taken", "ml", "m2", "m3", "m4" ]
[ true, false, false, false, false, false, false, false ]
1,570
3,566
predictive_accuracy
accuracy_score
fl2000
**Author**: **Source**: Unknown - Date unknown **Please cite**: County data from the 2000 Presidential Election in Florida. Compiled by Brett Presnell Department of Statistics, University of Florida These data are derived from three sources, described below. As far as I am aware, you are free to use these d...
{0: [0 - county (nominal)], 1: [1 - technology (nominal)], 2: [2 - columns (nominal)], 3: [3 - under (numeric)], 4: [4 - over (numeric)], 5: [5 - Bush (numeric)], 6: [6 - Gore (numeric)], 7: [7 - Browne (numeric)], 8: [8 - Nader (numeric)], 9: [9 - Harris (numeric)], 10: [10 - Hagelin (numeric)], 11: [11 - B...
{'MajorityClassSize': 41.0, 'MaxNominalAttDistinctValues': 5.0, 'MinorityClassSize': 1.0, 'NumberOfClasses': 5.0, 'NumberOfFeatures': 16.0, 'NumberOfInstances': 67.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 14.0, 'NumberOfSymbolicFeatures': 2.0, 'cos...
fl2000
[ "columns", "under", "over", "Bush", "Gore", "Browne", "Nader", "Harris", "Hagelin", "Buchanan", "McReynolds", "Phillips", "Moorehead", "Chote", "McCarthy" ]
[ true, false, false, false, false, false, false, false, false, false, false, false, false, false, false ]
1,571
3,576
predictive_accuracy
accuracy_score
sleuth_ex2015
**Author**: **Source**: Unknown - Date unknown **Please cite**: Contains 110 data sets from the book 'The Statistical Sleuth' by Fred Ramsey and Dan Schafer; Duxbury Press, 1997. (schafer@stat.orst.edu) [14/Oct/97] (172k) Note: description taken from this web site: http://lib.stat.cmu.edu/datasets/ File: ../...
{0: [0 - owl (nominal)], 1: [1 - pctring1 (numeric)], 2: [2 - pctring2 (numeric)], 3: [3 - pctring3 (numeric)], 4: [4 - pctring4 (numeric)], 5: [5 - pctring5 (numeric)], 6: [6 - pctring6 (numeric)], 7: [7 - pctring7 (numeric)]}
{'MajorityClassSize': 30.0, 'MaxNominalAttDistinctValues': 2.0, 'MinorityClassSize': 30.0, 'NumberOfClasses': 2.0, 'NumberOfFeatures': 8.0, 'NumberOfInstances': 60.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 7.0, 'NumberOfSymbolicFeatures': 1.0, 'cost...
sleuth_ex2015
[ "pctring1", "pctring2", "pctring3", "pctring4", "pctring5", "pctring6", "pctring7" ]
[ false, false, false, false, false, false, false ]
1,572