uid int64 2 364k | orig_metric stringclasses 30
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values | dataset_name stringlengths 2 124 | dataset_description stringlengths 3 13k ⌀ | dataset_features stringlengths 41 3.57M | task_description stringlengths 627 762 | task_name stringlengths 2 124 | attribute_names listlengths 0 100k | categorical_indicator listlengths 0 100k | __index_level_0__ int64 0 3.8k |
|---|---|---|---|---|---|---|---|---|---|---|
2,272 | 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,
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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)],
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2: [2 - att3 (numeric)],
3: [3 - att4 (numeric)],
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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,
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'NumberOfClasses': 10.0,
'NumberOfFeatures': 65.0,
'NumberOfInstances': 2000.0,
'NumberOfInstancesWithMissingValues': 0.0,
'NumberOfMissingValues': 0.0,
'NumberOfNumericFeatures': 64.0,
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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)],
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3: [3 - Travel_cost (numeric)],
4: [4 - Access_road (nominal)],
5: [5 - Active (nominal)],
6: [6 - Passive (nominal)],
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8: [8 - Trips (nominal)]} | {'MajorityClassSize': 318.0,
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'c... | braziltourism | [
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2,352 | predictive_accuracy | accuracy_score | meta_all.arff | null | {0: [0 - openml_task_id (numeric)],
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2: [2 - meta_J48.00001.ErrRate (numeric)],
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5: [5 - meta_NBAUC (numeric)],
6: [6 - meta_DecisionStumpKappa (numeric)],
7: [7 - meta_HoeffdingDDM.warni... | {'MajorityClassSize': 42.0,
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'NumberOfSymbolicFeatures': 1.0,
'cos... | meta_all.arff | [
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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,
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'... | abalone | [
"Sex",
"Length",
"Diameter",
"Height",
"Whole_weight",
"Shucked_weight",
"Viscera_weight",
"Shell_weight"
] | [
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] | 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,
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'cos... | meta_ensembles.arff | [
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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,
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'... | yeast | [
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"mit",
"erl",
"pox",
"vac",
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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)],
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'... | abalone | [
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"Length",
"Diameter",
"Height",
"Whole_weight",
"Shucked_weight",
"Viscera_weight",
"Shell_weight"
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false,
false,
false,
false,
false,
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] | 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 | [
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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,
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'NumberOfInstancesWithMissingValues': 20.0,
'NumberOfMissingValues': 20.0,
'NumberOfNumericFeatures': 15.0,
'NumberOfSymbolicFeatures': 2.0... | baseball | [
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"Hits",
"Doubles",
"Triples",
"Home_runs",
"RBIs",
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"Strikeouts",
"Batting_average",
"On_base_pct",
"Slugging_pct",
"Fielding_ave",
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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 | [
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f... | 1,468 |
2,275 | predictive_accuracy | accuracy_score | meta_instanceincremental.arff | null | {0: [0 - openml_task_id (numeric)],
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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)],
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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,
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'NumberOfFeatures': 14.0,
'NumberOfInstances': 178.0,
'NumberOfInstancesWithMissingValues': 0.0,
'NumberOfMissingValues': 0.0,
'NumberOfNumericFeatures': 13.0,
'NumberOfSymbolicFeatures': 1.0,
'c... | wine | [
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"Malic_acid",
"Ash",
"Alcalinity_of_ash",
"Magnesium",
"Total_phenols",
"Flavanoids",
"Nonflavanoid_phenols",
"Proanthocyanins",
"Color_intensity",
"Hue",
"OD280%2FOD315_of_diluted_wines",
"Proline"
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false,
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false,
false,
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false,
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] | 1,470 |
2,353 | predictive_accuracy | accuracy_score | meta_batchincremental.arff | null | {0: [0 - openml_task_id (numeric)],
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2: [2 - meta_J48.00001.ErrRate (numeric)],
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5: [5 - meta_NBAUC (numeric)],
6: [6 - meta_DecisionStumpKappa (numeric)],
7: [7 - meta_HoeffdingDDM.warni... | {'MajorityClassSize': 50.0,
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2,355 | predictive_accuracy | accuracy_score | meta_instanceincremental.arff | null | {0: [0 - openml_task_id (numeric)],
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2: [2 - meta_J48.00001.ErrRate (numeric)],
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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.
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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
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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
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2,354 | predictive_accuracy | accuracy_score | meta_ensembles.arff | null | {0: [0 - openml_task_id (numeric)],
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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
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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)],
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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)],
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'c... | braziltourism | [
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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)**
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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)
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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",
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2,977 | predictive_accuracy | accuracy_score | meta_batchincremental.arff | null | {0: [0 - openml_task_id (numeric)],
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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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true,
true,
true,
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true,
true,
true,
true,
true,
true,
true,
true,
true... | 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,
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false,
false,
false,
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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,
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false,
false,
false,
false,
false,
false,
false,
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false,
false,
false,
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false,
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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"... | [
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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,
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false,
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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",
"... | [
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false,
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false,
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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",
... | [
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false,
false,
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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",
"... | [
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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... | [
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false,
false,
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] | 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... | [
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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"
] | [
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true,
true,
true,
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] | 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",
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"F6R",
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"F13S",
"F14R",
"F14S",
"F15R",
"F15S",
"F16R",
"F16S",
"F17R",
"F17... | [
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false,
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false,
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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",
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"F6attr",
"A7attr",
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"C9attr",
"D10attr",
"E11attr",
"F12attr",
"A13attr",
"B14attr",
"C15attr",
"D16attr",
"E17attr",
"F18attr",
"A19attr",
"B20attr",
... | [
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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",
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"F13S",
"F14R",
"F14S",
"F15R",
"F15S",
"F16R",
"F16S",
"F17R",
"F17... | [
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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"
] | [
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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... | [
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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... | [
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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",
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"oz16",
"oz17",
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"oz23",
"oz24",
"oz25",
"oz26",
"oz27",
"oz28",
"oz29",
"oz30",
"oz31",
"oz32",
"oz33... | [
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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 |
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