Datasets:
asingh15
/
openml

Dataset card Data Studio Files
xet
 Community
1
uid
int64
2
364k
orig_metric
stringclasses
30 values
sklearn_metric
stringclasses
9 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
5,174
mean_absolute_error
mean_absolute_error
sensory
**Author**: **Source**: Unknown - Date unknown **Please cite**: Data for the sensory evaluation experiment in Brien, C.J. and Payne, R.W. (1996) Tiers, structure formulae and the analysis of complicated experiments. submitted for publication. The experiment involved two phases. In the field phase a viticultu...
{0: [0 - Occasion (nominal)], 1: [1 - Judges (nominal)], 2: [2 - Interval (nominal)], 3: [3 - Sittings (nominal)], 4: [4 - Position (nominal)], 5: [5 - Squares (nominal)], 6: [6 - Rows (nominal)], 7: [7 - Columns (nominal)], 8: [8 - Halfplot (nominal)], 9: [9 - Trellis (nominal)], 10: [10 - Method (nominal)],...
{'MajorityClassSize': nan, 'MaxNominalAttDistinctValues': 6.0, 'MinorityClassSize': nan, 'NumberOfClasses': 0.0, 'NumberOfFeatures': 12.0, 'NumberOfInstances': 576.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 1.0, 'NumberOfSymbolicFeatures': 11.0, 'cos...
sensory
[ "Occasion", "Judges", "Interval", "Sittings", "Position", "Squares", "Rows", "Columns", "Halfplot", "Trellis", "Method" ]
[ true, true, true, true, true, true, true, true, true, true, true ]
514
146,875
predictive_accuracy
accuracy_score
heart
**Author**: Laboratory of Artificial Intelligence and Computer Science of the University of Porto (LIACC) libSVM","AAD group **Source**: [original](http://www.csie.ntu.edu.tw/~cjlin/libsvmtools/datasets/binary.html) - Date unknown **Please cite**: #Dataset from the LIBSVM data repository. Preprocessing: scal...
{0: [0 - att_1 (numeric)], 1: [1 - att_2 (numeric)], 2: [2 - att_3 (numeric)], 3: [3 - att_4 (numeric)], 4: [4 - att_5 (numeric)], 5: [5 - att_6 (numeric)], 6: [6 - att_7 (numeric)], 7: [7 - att_8 (numeric)], 8: [8 - att_9 (numeric)], 9: [9 - att_10 (numeric)], 10: [10 - att_11 (numeric)], 11: [11 - att_12 (...
{'MajorityClassSize': nan, 'MaxNominalAttDistinctValues': nan, 'MinorityClassSize': nan, 'NumberOfClasses': 0.0, 'NumberOfFeatures': 14.0, 'NumberOfInstances': 270.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 14.0, 'NumberOfSymbolicFeatures': 0.0, 'cos...
heart
[ "att_1", "att_2", "att_3", "att_4", "att_5", "att_6", "att_7", "att_8", "att_9", "att_10", "att_11", "att_12", "att_13" ]
[ false, false, false, false, false, false, false, false, false, false, false, false, false ]
515
146,868
predictive_accuracy
accuracy_score
svmguide1
**Author**: Chih-Wei Hsu","Chih-Chung Chang","and Chih-Jen Lin. libSVM","AAD group **Source**: [original](http://www.csie.ntu.edu.tw/~cjlin/libsvmtools/datasets/binary.html) - Date unknown **Please cite**: Chih-Wei Hsu, Chih-Chung Chang, and Chih-Jen Lin. A practical guide to support vector classification. Techni...
{0: [0 - att_1 (numeric)], 1: [1 - att_2 (numeric)], 2: [2 - att_3 (numeric)], 3: [3 - att_4 (numeric)], 4: [4 - class (numeric)]}
{'MajorityClassSize': nan, 'MaxNominalAttDistinctValues': nan, 'MinorityClassSize': nan, 'NumberOfClasses': 0.0, 'NumberOfFeatures': 5.0, 'NumberOfInstances': 7089.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 5.0, 'NumberOfSymbolicFeatures': 0.0, 'cost...
svmguide1
[ "att_1", "att_2", "att_3", "att_4" ]
[ false, false, false, false ]
516
146,830
predictive_accuracy
accuracy_score
tr11.wc
null
{0: [0 - outfit (numeric)], 1: [1 - hasn (numeric)], 2: [2 - calm (numeric)], 3: [3 - gene (numeric)], 4: [4 - resettl (numeric)], 5: [5 - lotteri (numeric)], 6: [6 - privileg (numeric)], 7: [7 - junior (numeric)], 8: [8 - withdrawn (numeric)], 9: [9 - chok (numeric)], 10: [10 - compaq (numeric)], 11: [11 - ...
{'MajorityClassSize': 132.0, 'MaxNominalAttDistinctValues': 9.0, 'MinorityClassSize': 6.0, 'NumberOfClasses': 9.0, 'NumberOfFeatures': 6430.0, 'NumberOfInstances': 414.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 6429.0, 'NumberOfSymbolicFeatures': 1.0,...
tr11.wc
[ "outfit", "hasn", "calm", "gene", "resettl", "lotteri", "privileg", "junior", "withdrawn", "chok", "compaq", "noi", "colombia", "radioact", "neutron", "npc", "disabl", "macedonian", "eman", "skopje", "volkov", "appall", "sidelin", "titanium", "quasi", "league", "n...
[ false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, f...
517
146,842
predictive_accuracy
accuracy_score
oh10.wc
null
{0: [0 - sudden (numeric)], 1: [1 - gland (numeric)], 2: [2 - signific (numeric)], 3: [3 - penetr (numeric)], 4: [4 - hepat (numeric)], 5: [5 - fusion (numeric)], 6: [6 - agenc (numeric)], 7: [7 - rest (numeric)], 8: [8 - seropreval (numeric)], 9: [9 - nucleotid (numeric)], 10: [10 - echocardiographi (numeric...
{'MajorityClassSize': 165.0, 'MaxNominalAttDistinctValues': 10.0, 'MinorityClassSize': 52.0, 'NumberOfClasses': 10.0, 'NumberOfFeatures': 3239.0, 'NumberOfInstances': 1050.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 3238.0, 'NumberOfSymbolicFeatures': ...
oh10.wc
[ "sudden", "gland", "signific", "penetr", "hepat", "fusion", "agenc", "rest", "seropreval", "nucleotid", "echocardiographi", "decision", "agent", "0", "placem", "environ", "obstetr", "vagin", "overview", "cytokin", "reconstitut", "discharg", "f", "ileal", "g", "clind...
[ false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, f...
518
5,187
mean_absolute_error
mean_absolute_error
kdd_el_nino-small
**Author**: **Source**: Unknown - Date unknown **Please cite**: El Nino Data Data Type spatio-temporal Abstract The data set contains oceanographic and surface meteorological readings taken from a series of buoys positioned throughout the equatorial Pacific. The data is expected to aid in the understanding...
{0: [0 - buoy (nominal)], 1: [1 - day (nominal)], 2: [2 - latitude (numeric)], 3: [3 - longitude (numeric)], 4: [4 - zon_winds (numeric)], 5: [5 - mer_winds (numeric)], 6: [6 - humidity (numeric)], 7: [7 - air_temp (numeric)], 8: [8 - s_s_temp (numeric)]}
{'MajorityClassSize': nan, 'MaxNominalAttDistinctValues': 59.0, 'MinorityClassSize': nan, 'NumberOfClasses': 0.0, 'NumberOfFeatures': 9.0, 'NumberOfInstances': 782.0, 'NumberOfInstancesWithMissingValues': 214.0, 'NumberOfMissingValues': 539.0, 'NumberOfNumericFeatures': 7.0, 'NumberOfSymbolicFeatures': 2.0, '...
kdd_el_nino-small
[ "buoy", "day", "latitude", "longitude", "zon_winds", "mer_winds", "humidity", "air_temp" ]
[ true, true, false, false, false, false, false, false ]
519
5,181
mean_absolute_error
mean_absolute_error
analcatdata_apnea3
**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 - Automatic (nominal)], 1: [1 - Scorer_2 (nominal)], 2: [2 - Subject (numeric)], 3: [3 - Count (numeric)]}
{'MajorityClassSize': nan, 'MaxNominalAttDistinctValues': 5.0, 'MinorityClassSize': nan, 'NumberOfClasses': 0.0, 'NumberOfFeatures': 4.0, 'NumberOfInstances': 450.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 2.0, 'NumberOfSymbolicFeatures': 2.0, 'cost_...
analcatdata_apnea3
[ "Automatic", "Scorer_2", "Subject" ]
[ true, true, false ]
520
5,180
mean_absolute_error
mean_absolute_error
kidney
**Author**: McGilchrist and Aisbett **Source**: [StatLib](http://lib.stat.cmu.edu/datasets/) - 1999 **Please cite**: Data on the recurrence times to infection, at the point of insertion of the catheter, for kidney patients using portable dialysis equipment. Catheters may be removed for reasons other than infect...
{0: [0 - patient (numeric)], 1: [1 - time (numeric)], 2: [2 - status (nominal)], 3: [3 - age (numeric)], 4: [4 - sex (nominal)], 5: [5 - disease_type (nominal)], 6: [6 - frailty (numeric)]}
{'MajorityClassSize': nan, 'MaxNominalAttDistinctValues': 4.0, 'MinorityClassSize': nan, 'NumberOfClasses': 0.0, 'NumberOfFeatures': 7.0, 'NumberOfInstances': 76.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 4.0, 'NumberOfSymbolicFeatures': 3.0, 'cost_m...
kidney
[ "patient", "time", "status", "age", "sex", "disease_type" ]
[ false, false, true, false, true, true ]
521
5,171
mean_absolute_error
mean_absolute_error
boston_corrected
**Author**: **Source**: Unknown - Date unknown **Please cite**:
{0: [0 - OBS. (numeric)], 1: [1 - TOWN (nominal)], 2: [2 - TOWN_ID (numeric)], 3: [3 - TRACT (numeric)], 4: [4 - LON (numeric)], 5: [5 - LAT (numeric)], 6: [6 - MEDV (numeric)], 7: [7 - CMEDV (numeric)], 8: [8 - CRIM (numeric)], 9: [9 - ZN (numeric)], 10: [10 - INDUS (numeric)], 11: [11 - CHAS (nominal)], 1...
{'MajorityClassSize': nan, 'MaxNominalAttDistinctValues': 92.0, 'MinorityClassSize': nan, 'NumberOfClasses': 0.0, 'NumberOfFeatures': 21.0, 'NumberOfInstances': 506.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 18.0, 'NumberOfSymbolicFeatures': 3.0, 'co...
boston_corrected
[ "TOWN", "TOWN_ID", "TRACT", "LON", "LAT", "MEDV", "CMEDV", "CRIM", "ZN", "INDUS", "CHAS", "NOX", "RM", "AGE", "DIS", "RAD", "TAX", "PTRATIO", "B" ]
[ true, false, false, false, false, false, false, false, false, false, true, false, false, false, false, true, false, false, false ]
522
5,191
mean_absolute_error
mean_absolute_error
kdd_coil_2
**Author**: **Source**: Unknown - Date unknown **Please cite**: %%%%%%%%%%%%%%%%%%% Data-Description % %%%%%%%%%%%%%%%%%%% COIL 1999 Competition Data Data Type multivariate Abstract This data set is from the 1999 Computational Intelligence and Learning (COIL) competition. The data contains measurements of...
{0: [0 - season (nominal)], 1: [1 - river_size (nominal)], 2: [2 - fluid_velocity (nominal)], 3: [3 - concentration_1 (numeric)], 4: [4 - concentration_2 (numeric)], 5: [5 - concentration_3 (numeric)], 6: [6 - concentration_4 (numeric)], 7: [7 - concentration_5 (numeric)], 8: [8 - concentration_6 (numeric)], 9...
{'MajorityClassSize': nan, 'MaxNominalAttDistinctValues': 4.0, 'MinorityClassSize': nan, 'NumberOfClasses': 0.0, 'NumberOfFeatures': 12.0, 'NumberOfInstances': 316.0, 'NumberOfInstancesWithMissingValues': 34.0, 'NumberOfMissingValues': 56.0, 'NumberOfNumericFeatures': 9.0, 'NumberOfSymbolicFeatures': 3.0, 'co...
kdd_coil_2
[ "season", "river_size", "fluid_velocity", "concentration_1", "concentration_2", "concentration_3", "concentration_4", "concentration_5", "concentration_6", "concentration_7", "concentration_8" ]
[ true, true, true, false, false, false, false, false, false, false, false ]
523
146,826
predictive_accuracy
accuracy_score
tr45.wc
null
{0: [0 - sunni (numeric)], 1: [1 - interbank (numeric)], 2: [2 - rig (numeric)], 3: [3 - dlouhi (numeric)], 4: [4 - bratislava (numeric)], 5: [5 - librari (numeric)], 6: [6 - number (numeric)], 7: [7 - contamin (numeric)], 8: [8 - mold (numeric)], 9: [9 - norm (numeric)], 10: [10 - mobil (numeric)], 11: [11 ...
{'MajorityClassSize': 160.0, 'MaxNominalAttDistinctValues': 10.0, 'MinorityClassSize': 14.0, 'NumberOfClasses': 10.0, 'NumberOfFeatures': 8262.0, 'NumberOfInstances': 690.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 8261.0, 'NumberOfSymbolicFeatures': 1...
tr45.wc
[ "sunni", "interbank", "rig", "dlouhi", "bratislava", "librari", "number", "contamin", "mold", "norm", "mobil", "sens", "plankton", "ash", "workstat", "cabin", "sunken", "tengiz", "cove", "tragedi", "alloi", "fluid", "escort", "allot", "curi", "tac", "komsomolet", ...
[ false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, f...
524
146,888
predictive_accuracy
accuracy_score
svmguide3
**Author**: Chih-Wei Hsu","Chih-Chung Chang","and Chih-Jen Lin. libSVM","AAD group **Source**: [original](http://www.csie.ntu.edu.tw/~cjlin/libsvmtools/datasets/binary.html) - Date unknown **Please cite**: #Dataset from the LIBSVM data repository. Preprocessing: Original data: someone from Germany working wi...
{0: [0 - att_1 (numeric)], 1: [1 - att_2 (numeric)], 2: [2 - att_3 (numeric)], 3: [3 - att_4 (numeric)], 4: [4 - att_5 (numeric)], 5: [5 - att_6 (numeric)], 6: [6 - att_7 (numeric)], 7: [7 - att_8 (numeric)], 8: [8 - att_9 (numeric)], 9: [9 - att_10 (numeric)], 10: [10 - att_11 (numeric)], 11: [11 - att_12 (...
{'MajorityClassSize': nan, 'MaxNominalAttDistinctValues': nan, 'MinorityClassSize': nan, 'NumberOfClasses': 0.0, 'NumberOfFeatures': 23.0, 'NumberOfInstances': 1243.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 23.0, 'NumberOfSymbolicFeatures': 0.0, 'co...
svmguide3
[ "att_1", "att_2", "att_3", "att_4", "att_5", "att_6", "att_7", "att_8", "att_9", "att_10", "att_11", "att_12", "att_13", "att_14", "att_15", "att_16", "att_17", "att_18", "att_19", "att_20", "att_21", "att_22" ]
[ false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false ]
525
5,166
mean_absolute_error
mean_absolute_error
colleges_usnews
**Author**: **Source**: Unknown - Date unknown **Please cite**: The USNEWS dataset for the ASA Statistical Graphics Section's 1995 Data Analysis Exposition contains information on over 1300 American colleges and universities. The data may be obtained in either of two formats. USNEWS.DATA contains the raw dat...
{0: [0 - FICE (numeric)], 1: [1 - College_name (nominal)], 2: [2 - State (nominal)], 3: [3 - Public/private_indicator (numeric)], 4: [4 - Average_Math_SAT_score (numeric)], 5: [5 - Average_Verbal_SAT_score (numeric)], 6: [6 - Average_Combined_SAT_score (numeric)], 7: [7 - Average_ACT_score (numeric)], 8: [8 - F...
{'MajorityClassSize': nan, 'MaxNominalAttDistinctValues': 51.0, 'MinorityClassSize': nan, 'NumberOfClasses': 0.0, 'NumberOfFeatures': 33.0, 'NumberOfInstances': 1302.0, 'NumberOfInstancesWithMissingValues': 1144.0, 'NumberOfMissingValues': 7928.0, 'NumberOfNumericFeatures': 32.0, 'NumberOfSymbolicFeatures': 1....
colleges_usnews
[ "State", "Public/private_indicator", "Average_Math_SAT_score", "Average_Verbal_SAT_score", "Average_Combined_SAT_score", "Average_ACT_score", "First_quartile-Math_SAT", "Third_quartile-Math_SAT", "First_quartile-Verbal_SAT", "Third_quartile-Verbal_SAT", "First_quartile-ACT", "Third_quartile-AC...
[ true, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false ]
526
146,867
predictive_accuracy
accuracy_score
colon-cancer
**Author**: U. Alon","N. Barkai","D. A. Notterman","K. Gish","S.Ybarra","D.Mack","and A. J. Levine. libSVM","AAD group **Source**: [original](http://www.csie.ntu.edu.tw/~cjlin/libsvmtools/datasets/binary.html) - Date unknown **Please cite**: U. Alon, N. Barkai, D. A. Notterman, K. Gish, S.Ybarra, D.Mack, and A. J...
{0: [0 - att_1 (numeric)], 1: [1 - att_2 (numeric)], 2: [2 - att_3 (numeric)], 3: [3 - att_4 (numeric)], 4: [4 - att_5 (numeric)], 5: [5 - att_6 (numeric)], 6: [6 - att_7 (numeric)], 7: [7 - att_8 (numeric)], 8: [8 - att_9 (numeric)], 9: [9 - att_10 (numeric)], 10: [10 - att_11 (numeric)], 11: [11 - att_12 (...
{'MajorityClassSize': nan, 'MaxNominalAttDistinctValues': nan, 'MinorityClassSize': nan, 'NumberOfClasses': 0.0, 'NumberOfFeatures': 2001.0, 'NumberOfInstances': 62.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 2001.0, 'NumberOfSymbolicFeatures': 0.0, '...
colon-cancer
[ "att_1", "att_2", "att_3", "att_4", "att_5", "att_6", "att_7", "att_8", "att_9", "att_10", "att_11", "att_12", "att_13", "att_14", "att_15", "att_16", "att_17", "att_18", "att_19", "att_20", "att_21", "att_22", "att_23", "att_24", "att_25", "att_26", "att_27", "...
[ false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, f...
527
146,828
predictive_accuracy
accuracy_score
tr31.wc
null
{0: [0 - cone (numeric)], 1: [1 - protection (numeric)], 2: [2 - wir (numeric)], 3: [3 - fright (numeric)], 4: [4 - resold (numeric)], 5: [5 - thirsti (numeric)], 6: [6 - isolina (numeric)], 7: [7 - lucho (numeric)], 8: [8 - wari (numeric)], 9: [9 - sermon (numeric)], 10: [10 - unwis (numeric)], 11: [11 - co...
{'MajorityClassSize': 352.0, 'MaxNominalAttDistinctValues': 7.0, 'MinorityClassSize': 2.0, 'NumberOfClasses': 7.0, 'NumberOfFeatures': 10129.0, 'NumberOfInstances': 927.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 10128.0, 'NumberOfSymbolicFeatures': 1....
tr31.wc
[ "cone", "protection", "wir", "fright", "resold", "thirsti", "isolina", "lucho", "wari", "sermon", "unwis", "commenc", "optic", "ah", "reservoir", "au", "uninjur", "deflat", "enclav", "narcodollar", "delgado", "jakarta", "oxapampa", "yonsei", "modul", "labell", "in...
[ false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, f...
528
5,199
mean_absolute_error
mean_absolute_error
kdd_coil_6
**Author**: **Source**: Unknown - Date unknown **Please cite**: %%%%%%%%%%%%%%%%%%% Data-Description % %%%%%%%%%%%%%%%%%%% COIL 1999 Competition Data Data Type multivariate Abstract This data set is from the 1999 Computational Intelligence and Learning (COIL) competition. The data contains measurements of...
{0: [0 - season (nominal)], 1: [1 - river_size (nominal)], 2: [2 - fluid_velocity (nominal)], 3: [3 - concentration_1 (numeric)], 4: [4 - concentration_2 (numeric)], 5: [5 - concentration_3 (numeric)], 6: [6 - concentration_4 (numeric)], 7: [7 - concentration_5 (numeric)], 8: [8 - concentration_6 (numeric)], 9...
{'MajorityClassSize': nan, 'MaxNominalAttDistinctValues': 4.0, 'MinorityClassSize': nan, 'NumberOfClasses': 0.0, 'NumberOfFeatures': 12.0, 'NumberOfInstances': 316.0, 'NumberOfInstancesWithMissingValues': 34.0, 'NumberOfMissingValues': 56.0, 'NumberOfNumericFeatures': 9.0, 'NumberOfSymbolicFeatures': 3.0, 'co...
kdd_coil_6
[ "season", "river_size", "fluid_velocity", "concentration_1", "concentration_2", "concentration_3", "concentration_4", "concentration_5", "concentration_6", "concentration_7", "concentration_8" ]
[ true, true, true, false, false, false, false, false, false, false, false ]
529
146,879
predictive_accuracy
accuracy_score
splice
**Author**: Delve Datasets libSVM","AAD group **Source**: [original](http://www.csie.ntu.edu.tw/~cjlin/libsvmtools/datasets/binary.html) - Date unknown **Please cite**: #Dataset from the LIBSVM data repository. Preprocessing: scaled to [-1,1]
{0: [0 - att_1 (numeric)], 1: [1 - att_2 (numeric)], 2: [2 - att_3 (numeric)], 3: [3 - att_4 (numeric)], 4: [4 - att_5 (numeric)], 5: [5 - att_6 (numeric)], 6: [6 - att_7 (numeric)], 7: [7 - att_8 (numeric)], 8: [8 - att_9 (numeric)], 9: [9 - att_10 (numeric)], 10: [10 - att_11 (numeric)], 11: [11 - att_12 (...
{'MajorityClassSize': nan, 'MaxNominalAttDistinctValues': nan, 'MinorityClassSize': nan, 'NumberOfClasses': 0.0, 'NumberOfFeatures': 61.0, 'NumberOfInstances': 3175.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 61.0, 'NumberOfSymbolicFeatures': 0.0, 'co...
splice
[ "att_1", "att_2", "att_3", "att_4", "att_5", "att_6", "att_7", "att_8", "att_9", "att_10", "att_11", "att_12", "att_13", "att_14", "att_15", "att_16", "att_17", "att_18", "att_19", "att_20", "att_21", "att_22", "att_23", "att_24", "att_25", "att_26", "att_27", "...
[ false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, f...
530
5,190
mean_absolute_error
mean_absolute_error
kdd_coil_1
**Author**: **Source**: Unknown - Date unknown **Please cite**: %%%%%%%%%%%%%%%%%%% Data-Description % %%%%%%%%%%%%%%%%%%% COIL 1999 Competition Data Data Type multivariate Abstract This data set is from the 1999 Computational Intelligence and Learning (COIL) competition. The data contains measurements of...
{0: [0 - season (nominal)], 1: [1 - river_size (nominal)], 2: [2 - fluid_velocity (nominal)], 3: [3 - concentration_1 (numeric)], 4: [4 - concentration_2 (numeric)], 5: [5 - concentration_3 (numeric)], 6: [6 - concentration_4 (numeric)], 7: [7 - concentration_5 (numeric)], 8: [8 - concentration_6 (numeric)], 9...
{'MajorityClassSize': nan, 'MaxNominalAttDistinctValues': 4.0, 'MinorityClassSize': nan, 'NumberOfClasses': 0.0, 'NumberOfFeatures': 12.0, 'NumberOfInstances': 316.0, 'NumberOfInstancesWithMissingValues': 34.0, 'NumberOfMissingValues': 56.0, 'NumberOfNumericFeatures': 9.0, 'NumberOfSymbolicFeatures': 3.0, 'co...
kdd_coil_1
[ "season", "river_size", "fluid_velocity", "concentration_1", "concentration_2", "concentration_3", "concentration_4", "concentration_5", "concentration_6", "concentration_7", "concentration_8" ]
[ true, true, true, false, false, false, false, false, false, false, false ]
531
146,841
predictive_accuracy
accuracy_score
tr41.wc
null
{0: [0 - lighthous (numeric)], 1: [1 - conquest (numeric)], 2: [2 - algerian (numeric)], 3: [3 - banish (numeric)], 4: [4 - jerri (numeric)], 5: [5 - nationalist (numeric)], 6: [6 - evil (numeric)], 7: [7 - beirut (numeric)], 8: [8 - worrisom (numeric)], 9: [9 - stolen (numeric)], 10: [10 - durabl (numeric)],...
{'MajorityClassSize': 243.0, 'MaxNominalAttDistinctValues': 10.0, 'MinorityClassSize': 9.0, 'NumberOfClasses': 10.0, 'NumberOfFeatures': 7455.0, 'NumberOfInstances': 878.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 7454.0, 'NumberOfSymbolicFeatures': 1....
tr41.wc
[ "lighthous", "conquest", "algerian", "banish", "jerri", "nationalist", "evil", "beirut", "worrisom", "stolen", "durabl", "adburgham", "restart", "lee", "avonmouth", "wive", "exot", "tighter", "tenth", "polic", "diane", "perish", "altimet", "princeton", "eb", "diseas...
[ false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, f...
532
5,185
mean_absolute_error
mean_absolute_error
schlvote
**Author**: **Source**: Unknown - Date unknown **Please cite**: Dataset from Smoothing Methods in Statistics (ftp stat.cmu.edu/datasets) Simonoff, J.S. (1996). Smoothing Methods in Statistics. New York: Springer-Verlag.
{0: [0 - vote (nominal)], 1: [1 - tax_rate (numeric)], 2: [2 - budget (numeric)], 3: [3 - budget_change (numeric)], 4: [4 - tax_rate_change (numeric)], 5: [5 - wealth_per_student (numeric)]}
{'MajorityClassSize': nan, 'MaxNominalAttDistinctValues': 2.0, 'MinorityClassSize': nan, 'NumberOfClasses': 0.0, 'NumberOfFeatures': 6.0, 'NumberOfInstances': 38.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 1.0, 'NumberOfNumericFeatures': 5.0, 'NumberOfSymbolicFeatures': 1.0, 'cost_m...
schlvote
[ "vote", "tax_rate", "budget", "budget_change", "tax_rate_change" ]
[ true, false, false, false, false ]
533
5,508
predictive_accuracy
accuracy_score
la1s.wc
null
{0: [0 - aa (numeric)], 1: [1 - aaron (numeric)], 2: [2 - ab (numeric)], 3: [3 - aback (numeric)], 4: [4 - abandon (numeric)], 5: [5 - abat (numeric)], 6: [6 - abbe (numeric)], 7: [7 - abbrevi (numeric)], 8: [8 - abc (numeric)], 9: [9 - abdel (numeric)], 10: [10 - abdi (numeric)], 11: [11 - abdomen (numeric)...
{'MajorityClassSize': 943.0, 'MaxNominalAttDistinctValues': 6.0, 'MinorityClassSize': 273.0, 'NumberOfClasses': 6.0, 'NumberOfFeatures': 13196.0, 'NumberOfInstances': 3204.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 13195.0, 'NumberOfSymbolicFeatures':...
la1s.wc
[ "aa", "aaron", "ab", "aback", "abandon", "abat", "abbe", "abbrevi", "abc", "abdel", "abdi", "abdomen", "abdomin", "abduct", "abdul", "abdullah", "abe", "aberr", "abet", "abid", "abil", "ablaz", "able", "abnorm", "aboard", "abolish", "abort", "abound", "abram",...
[ false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, f...
534
5,198
mean_absolute_error
mean_absolute_error
kdd_coil_5
**Author**: **Source**: Unknown - Date unknown **Please cite**: %%%%%%%%%%%%%%%%%%% Data-Description % %%%%%%%%%%%%%%%%%%% COIL 1999 Competition Data Data Type multivariate Abstract This data set is from the 1999 Computational Intelligence and Learning (COIL) competition. The data contains measurements of...
{0: [0 - season (nominal)], 1: [1 - river_size (nominal)], 2: [2 - fluid_velocity (nominal)], 3: [3 - concentration_1 (numeric)], 4: [4 - concentration_2 (numeric)], 5: [5 - concentration_3 (numeric)], 6: [6 - concentration_4 (numeric)], 7: [7 - concentration_5 (numeric)], 8: [8 - concentration_6 (numeric)], 9...
{'MajorityClassSize': nan, 'MaxNominalAttDistinctValues': 4.0, 'MinorityClassSize': nan, 'NumberOfClasses': 0.0, 'NumberOfFeatures': 12.0, 'NumberOfInstances': 316.0, 'NumberOfInstancesWithMissingValues': 34.0, 'NumberOfMissingValues': 56.0, 'NumberOfNumericFeatures': 9.0, 'NumberOfSymbolicFeatures': 3.0, 'co...
kdd_coil_5
[ "season", "river_size", "fluid_velocity", "concentration_1", "concentration_2", "concentration_3", "concentration_4", "concentration_5", "concentration_6", "concentration_7", "concentration_8" ]
[ true, true, true, false, false, false, false, false, false, false, false ]
535
5,192
mean_absolute_error
mean_absolute_error
kdd_coil_3
**Author**: **Source**: Unknown - Date unknown **Please cite**: %%%%%%%%%%%%%%%%%%% Data-Description % %%%%%%%%%%%%%%%%%%% COIL 1999 Competition Data Data Type multivariate Abstract This data set is from the 1999 Computational Intelligence and Learning (COIL) competition. The data contains measurements of...
{0: [0 - season (nominal)], 1: [1 - river_size (nominal)], 2: [2 - fluid_velocity (nominal)], 3: [3 - concentration_1 (numeric)], 4: [4 - concentration_2 (numeric)], 5: [5 - concentration_3 (numeric)], 6: [6 - concentration_4 (numeric)], 7: [7 - concentration_5 (numeric)], 8: [8 - concentration_6 (numeric)], 9...
{'MajorityClassSize': nan, 'MaxNominalAttDistinctValues': 4.0, 'MinorityClassSize': nan, 'NumberOfClasses': 0.0, 'NumberOfFeatures': 12.0, 'NumberOfInstances': 316.0, 'NumberOfInstancesWithMissingValues': 34.0, 'NumberOfMissingValues': 56.0, 'NumberOfNumericFeatures': 9.0, 'NumberOfSymbolicFeatures': 3.0, 'co...
kdd_coil_3
[ "season", "river_size", "fluid_velocity", "concentration_1", "concentration_2", "concentration_3", "concentration_4", "concentration_5", "concentration_6", "concentration_7", "concentration_8" ]
[ true, true, true, false, false, false, false, false, false, false, false ]
536
5,076
mean_absolute_error
mean_absolute_error
us_crime
**Author**: **Source**: Unknown - 2009 **Please cite**: Title: Communities and Crime Abstract: Communities within the United States. The data combines socio-economic data from the 1990 US Census, law enforcement data from the 1990 US LEMAS survey, and crime data from the 1995 FBI UCR. Data Set Characteri...
{0: [0 - state (numeric)], 1: [1 - county (numeric)], 2: [2 - community (numeric)], 3: [3 - communityname (string)], 4: [4 - fold (numeric)], 5: [5 - population (numeric)], 6: [6 - householdsize (numeric)], 7: [7 - racepctblack (numeric)], 8: [8 - racePctWhite (numeric)], 9: [9 - racePctAsian (numeric)], 10: ...
{'MajorityClassSize': nan, 'MaxNominalAttDistinctValues': nan, 'MinorityClassSize': nan, 'NumberOfClasses': 0.0, 'NumberOfFeatures': 128.0, 'NumberOfInstances': 1994.0, 'NumberOfInstancesWithMissingValues': 1871.0, 'NumberOfMissingValues': 39202.0, 'NumberOfNumericFeatures': 127.0, 'NumberOfSymbolicFeatures': ...
us_crime
[ "state", "county", "community", "communityname", "fold", "population", "householdsize", "racepctblack", "racePctWhite", "racePctAsian", "racePctHisp", "agePct12t21", "agePct12t29", "agePct16t24", "agePct65up", "numbUrban", "pctUrban", "medIncome", "pctWWage", "pctWFarmSelf", ...
[ false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, f...
537
5,183
mean_absolute_error
mean_absolute_error
analcatdata_apnea1
**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 - Scorer_1 (nominal)], 1: [1 - Scorer_2 (nominal)], 2: [2 - Subject (numeric)], 3: [3 - Count (numeric)]}
{'MajorityClassSize': nan, 'MaxNominalAttDistinctValues': 5.0, 'MinorityClassSize': nan, 'NumberOfClasses': 0.0, 'NumberOfFeatures': 4.0, 'NumberOfInstances': 475.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 2.0, 'NumberOfSymbolicFeatures': 2.0, 'cost_...
analcatdata_apnea1
[ "Scorer_1", "Scorer_2", "Subject" ]
[ true, true, false ]
538
5,505
predictive_accuracy
accuracy_score
la2s.wc
null
{0: [0 - aa (numeric)], 1: [1 - aaa (numeric)], 2: [2 - aaron (numeric)], 3: [3 - aase (numeric)], 4: [4 - ab (numeric)], 5: [5 - abandon (numeric)], 6: [6 - abat (numeric)], 7: [7 - abbe (numeric)], 8: [8 - abc (numeric)], 9: [9 - abdi (numeric)], 10: [10 - abdomen (numeric)], 11: [11 - abdomin (numeric)], ...
{'MajorityClassSize': 905.0, 'MaxNominalAttDistinctValues': 6.0, 'MinorityClassSize': 248.0, 'NumberOfClasses': 6.0, 'NumberOfFeatures': 12433.0, 'NumberOfInstances': 3075.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 12432.0, 'NumberOfSymbolicFeatures':...
la2s.wc
[ "aa", "aaa", "aaron", "aase", "ab", "abandon", "abat", "abbe", "abc", "abdi", "abdomen", "abdomin", "abduct", "abdul", "abe", "abet", "abhorr", "abid", "abil", "able", "abnorm", "aboard", "abolish", "abolit", "abort", "abound", "abraham", "abram", "abroad", ...
[ false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, f...
539
5,197
mean_absolute_error
mean_absolute_error
kdd_coil_4
**Author**: **Source**: Unknown - Date unknown **Please cite**: %%%%%%%%%%%%%%%%%%% Data-Description % %%%%%%%%%%%%%%%%%%% COIL 1999 Competition Data Data Type multivariate Abstract This data set is from the 1999 Computational Intelligence and Learning (COIL) competition. The data contains measurements of...
{0: [0 - season (nominal)], 1: [1 - river_size (nominal)], 2: [2 - fluid_velocity (nominal)], 3: [3 - concentration_1 (numeric)], 4: [4 - concentration_2 (numeric)], 5: [5 - concentration_3 (numeric)], 6: [6 - concentration_4 (numeric)], 7: [7 - concentration_5 (numeric)], 8: [8 - concentration_6 (numeric)], 9...
{'MajorityClassSize': nan, 'MaxNominalAttDistinctValues': 4.0, 'MinorityClassSize': nan, 'NumberOfClasses': 0.0, 'NumberOfFeatures': 12.0, 'NumberOfInstances': 316.0, 'NumberOfInstancesWithMissingValues': 34.0, 'NumberOfMissingValues': 56.0, 'NumberOfNumericFeatures': 9.0, 'NumberOfSymbolicFeatures': 3.0, 'co...
kdd_coil_4
[ "season", "river_size", "fluid_velocity", "concentration_1", "concentration_2", "concentration_3", "concentration_4", "concentration_5", "concentration_6", "concentration_7", "concentration_8" ]
[ true, true, true, false, false, false, false, false, false, false, false ]
540
5,186
mean_absolute_error
mean_absolute_error
cpu_small
**Author**: **Source**: Unknown - Date unknown **Please cite**: The Computer Activity databases are a collection of computer systems activity measures. The data was collected from a Sun Sparcstation 20/712 with 128 Mbytes of memory running in a multi-user university department. Users would typically be doing a...
{0: [0 - lread (numeric)], 1: [1 - lwrite (numeric)], 2: [2 - scall (numeric)], 3: [3 - sread (numeric)], 4: [4 - swrite (numeric)], 5: [5 - fork (numeric)], 6: [6 - exec (numeric)], 7: [7 - rchar (numeric)], 8: [8 - wchar (numeric)], 9: [9 - runqsz (numeric)], 10: [10 - freemem (numeric)], 11: [11 - freeswa...
{'MajorityClassSize': nan, 'MaxNominalAttDistinctValues': nan, 'MinorityClassSize': nan, 'NumberOfClasses': 0.0, 'NumberOfFeatures': 13.0, 'NumberOfInstances': 8192.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 13.0, 'NumberOfSymbolicFeatures': 0.0, 'co...
cpu_small
[ "lread", "lwrite", "scall", "sread", "swrite", "fork", "exec", "rchar", "wchar", "runqsz", "freemem", "freeswap" ]
[ false, false, false, false, false, false, false, false, false, false, false, false ]
541
5,201
mean_absolute_error
mean_absolute_error
fri_c0_250_5
**Author**: **Source**: Unknown - Date unknown **Please cite**: The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as "fri_colinearintydegree_samplenumber_featurenumber". Friedman is the one of the most...
{0: [0 - oz1 (numeric)], 1: [1 - oz2 (numeric)], 2: [2 - oz3 (numeric)], 3: [3 - oz4 (numeric)], 4: [4 - oz5 (numeric)], 5: [5 - oz6 (numeric)]}
{'MajorityClassSize': nan, 'MaxNominalAttDistinctValues': nan, 'MinorityClassSize': nan, 'NumberOfClasses': 0.0, 'NumberOfFeatures': 6.0, 'NumberOfInstances': 250.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 6.0, 'NumberOfSymbolicFeatures': 0.0, 'cost_...
fri_c0_250_5
[ "oz1", "oz2", "oz3", "oz4", "oz5" ]
[ false, false, false, false, false ]
542
5,203
mean_absolute_error
mean_absolute_error
fri_c3_500_25
**Author**: **Source**: Unknown - Date unknown **Please cite**: The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as "fri_colinearintydegree_samplenumber_featurenumber". Friedman is the one of the most...
{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': 26.0, 'NumberOfInstances': 500.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 26.0, 'NumberOfSymbolicFeatures': 0.0, 'cos...
fri_c3_500_25
[ "oz1", "oz2", "oz3", "oz4", "oz5", "oz6", "oz7", "oz8", "oz9", "oz10", "oz11", "oz12", "oz13", "oz14", "oz15", "oz16", "oz17", "oz18", "oz19", "oz20", "oz21", "oz22", "oz23", "oz24", "oz25" ]
[ false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false ]
543
5,202
mean_absolute_error
mean_absolute_error
fri_c4_250_100
**Author**: **Source**: Unknown - Date unknown **Please cite**: The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as "fri_colinearintydegree_samplenumber_featurenumber". Friedman is the one of the most...
{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': 101.0, 'NumberOfInstances': 250.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 101.0, 'NumberOfSymbolicFeatures': 0.0, 'c...
fri_c4_250_100
[ "oz1", "oz2", "oz3", "oz4", "oz5", "oz6", "oz7", "oz8", "oz9", "oz10", "oz11", "oz12", "oz13", "oz14", "oz15", "oz16", "oz17", "oz18", "oz19", "oz20", "oz21", "oz22", "oz23", "oz24", "oz25", "oz26", "oz27", "oz28", "oz29", "oz30", "oz31", "oz32", "oz33...
[ false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, f...
544
146,837
predictive_accuracy
accuracy_score
la1s.wc
null
{0: [0 - aa (numeric)], 1: [1 - aaron (numeric)], 2: [2 - ab (numeric)], 3: [3 - aback (numeric)], 4: [4 - abandon (numeric)], 5: [5 - abat (numeric)], 6: [6 - abbe (numeric)], 7: [7 - abbrevi (numeric)], 8: [8 - abc (numeric)], 9: [9 - abdel (numeric)], 10: [10 - abdi (numeric)], 11: [11 - abdomen (numeric)...
{'MajorityClassSize': 943.0, 'MaxNominalAttDistinctValues': 6.0, 'MinorityClassSize': 273.0, 'NumberOfClasses': 6.0, 'NumberOfFeatures': 13196.0, 'NumberOfInstances': 3204.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 13195.0, 'NumberOfSymbolicFeatures':...
la1s.wc
[ "aa", "aaron", "ab", "aback", "abandon", "abat", "abbe", "abbrevi", "abc", "abdel", "abdi", "abdomen", "abdomin", "abduct", "abdul", "abdullah", "abe", "aberr", "abet", "abid", "abil", "ablaz", "able", "abnorm", "aboard", "abolish", "abort", "abound", "abram",...
[ false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, f...
545
5,204
mean_absolute_error
mean_absolute_error
fri_c1_500_25
**Author**: **Source**: Unknown - Date unknown **Please cite**: The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as "fri_colinearintydegree_samplenumber_featurenumber". Friedman is the one of the most...
{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': 26.0, 'NumberOfInstances': 500.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 26.0, 'NumberOfSymbolicFeatures': 0.0, 'cos...
fri_c1_500_25
[ "oz1", "oz2", "oz3", "oz4", "oz5", "oz6", "oz7", "oz8", "oz9", "oz10", "oz11", "oz12", "oz13", "oz14", "oz15", "oz16", "oz17", "oz18", "oz19", "oz20", "oz21", "oz22", "oz23", "oz24", "oz25" ]
[ false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false ]
546
5,200
mean_absolute_error
mean_absolute_error
kdd_coil_7
**Author**: **Source**: Unknown - Date unknown **Please cite**: %%%%%%%%%%%%%%%%%%% Data-Description % %%%%%%%%%%%%%%%%%%% COIL 1999 Competition Data Data Type multivariate Abstract This data set is from the 1999 Computational Intelligence and Learning (COIL) competition. The data contains measurements of...
{0: [0 - season (nominal)], 1: [1 - river_size (nominal)], 2: [2 - fluid_velocity (nominal)], 3: [3 - concentration_1 (numeric)], 4: [4 - concentration_2 (numeric)], 5: [5 - concentration_3 (numeric)], 6: [6 - concentration_4 (numeric)], 7: [7 - concentration_5 (numeric)], 8: [8 - concentration_6 (numeric)], 9...
{'MajorityClassSize': nan, 'MaxNominalAttDistinctValues': 4.0, 'MinorityClassSize': nan, 'NumberOfClasses': 0.0, 'NumberOfFeatures': 12.0, 'NumberOfInstances': 316.0, 'NumberOfInstancesWithMissingValues': 34.0, 'NumberOfMissingValues': 56.0, 'NumberOfNumericFeatures': 9.0, 'NumberOfSymbolicFeatures': 3.0, 'co...
kdd_coil_7
[ "season", "river_size", "fluid_velocity", "concentration_1", "concentration_2", "concentration_3", "concentration_4", "concentration_5", "concentration_6", "concentration_7", "concentration_8" ]
[ true, true, true, false, false, false, false, false, false, false, false ]
547
5,209
mean_absolute_error
mean_absolute_error
fri_c3_100_50
**Author**: **Source**: Unknown - Date unknown **Please cite**: The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as "fri_colinearintydegree_samplenumber_featurenumber". Friedman is the one of the most...
{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': 51.0, 'NumberOfInstances': 100.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 51.0, 'NumberOfSymbolicFeatures': 0.0, 'cos...
fri_c3_100_50
[ "oz1", "oz2", "oz3", "oz4", "oz5", "oz6", "oz7", "oz8", "oz9", "oz10", "oz11", "oz12", "oz13", "oz14", "oz15", "oz16", "oz17", "oz18", "oz19", "oz20", "oz21", "oz22", "oz23", "oz24", "oz25", "oz26", "oz27", "oz28", "oz29", "oz30", "oz31", "oz32", "oz33...
[ false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, f...
548
211,742
predictive_accuracy
accuracy_score
oh15.wc
null
{0: [0 - cluster (numeric)], 1: [1 - infus (numeric)], 2: [2 - gland (numeric)], 3: [3 - dopamin (numeric)], 4: [4 - phagocytosi (numeric)], 5: [5 - fetal (numeric)], 6: [6 - signific (numeric)], 7: [7 - penetr (numeric)], 8: [8 - hepat (numeric)], 9: [9 - cigarett (numeric)], 10: [10 - fusion (numeric)], 11...
{'MajorityClassSize': 157.0, 'MaxNominalAttDistinctValues': 10.0, 'MinorityClassSize': 53.0, 'NumberOfClasses': 10.0, 'NumberOfFeatures': 3101.0, 'NumberOfInstances': 913.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 3100.0, 'NumberOfSymbolicFeatures': 1...
oh15.wc
[ "cluster", "infus", "gland", "dopamin", "phagocytosi", "fetal", "signific", "penetr", "hepat", "cigarett", "fusion", "nitroprussid", "rifampin", "resist", "huvec", "rest", "quadricep", "goal", "hydroxi", "nucleotid", "echocardiographi", "agent", "0", "placem", "juli",...
[ false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, f...
549
146,834
predictive_accuracy
accuracy_score
la2s.wc
null
{0: [0 - aa (numeric)], 1: [1 - aaa (numeric)], 2: [2 - aaron (numeric)], 3: [3 - aase (numeric)], 4: [4 - ab (numeric)], 5: [5 - abandon (numeric)], 6: [6 - abat (numeric)], 7: [7 - abbe (numeric)], 8: [8 - abc (numeric)], 9: [9 - abdi (numeric)], 10: [10 - abdomen (numeric)], 11: [11 - abdomin (numeric)], ...
{'MajorityClassSize': 905.0, 'MaxNominalAttDistinctValues': 6.0, 'MinorityClassSize': 248.0, 'NumberOfClasses': 6.0, 'NumberOfFeatures': 12433.0, 'NumberOfInstances': 3075.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 12432.0, 'NumberOfSymbolicFeatures':...
la2s.wc
[ "aa", "aaa", "aaron", "aase", "ab", "abandon", "abat", "abbe", "abc", "abdi", "abdomen", "abdomin", "abduct", "abdul", "abe", "abet", "abhorr", "abid", "abil", "able", "abnorm", "aboard", "abolish", "abolit", "abort", "abound", "abraham", "abram", "abroad", ...
[ false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, f...
550
5,207
mean_absolute_error
mean_absolute_error
fri_c3_100_10
**Author**: **Source**: Unknown - Date unknown **Please cite**: The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as "fri_colinearintydegree_samplenumber_featurenumber". Friedman is the one of the most...
{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)]}
{'MajorityClassSize': nan, 'MaxNominalAttDistinctValues': nan, 'MinorityClassSize': nan, 'NumberOfClasses': 0.0, 'NumberOfFeatures': 11.0, 'NumberOfInstances': 100.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 11.0, 'NumberOfSymbolicFeatures': 0.0, 'cos...
fri_c3_100_10
[ "oz1", "oz2", "oz3", "oz4", "oz5", "oz6", "oz7", "oz8", "oz9", "oz10" ]
[ false, false, false, false, false, false, false, false, false, false ]
551
5,213
mean_absolute_error
mean_absolute_error
fri_c1_100_10
**Author**: **Source**: Unknown - Date unknown **Please cite**: The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as "fri_colinearintydegree_samplenumber_featurenumber". Friedman is the one of the most...
{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)]}
{'MajorityClassSize': nan, 'MaxNominalAttDistinctValues': nan, 'MinorityClassSize': nan, 'NumberOfClasses': 0.0, 'NumberOfFeatures': 11.0, 'NumberOfInstances': 100.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 11.0, 'NumberOfSymbolicFeatures': 0.0, 'cos...
fri_c1_100_10
[ "oz1", "oz2", "oz3", "oz4", "oz5", "oz6", "oz7", "oz8", "oz9", "oz10" ]
[ false, false, false, false, false, false, false, false, false, false ]
552
5,208
mean_absolute_error
mean_absolute_error
fri_c3_1000_25
**Author**: **Source**: Unknown - Date unknown **Please cite**: The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as "fri_colinearintydegree_samplenumber_featurenumber". Friedman is the one of the most...
{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': 26.0, 'NumberOfInstances': 1000.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 26.0, 'NumberOfSymbolicFeatures': 0.0, 'co...
fri_c3_1000_25
[ "oz1", "oz2", "oz3", "oz4", "oz5", "oz6", "oz7", "oz8", "oz9", "oz10", "oz11", "oz12", "oz13", "oz14", "oz15", "oz16", "oz17", "oz18", "oz19", "oz20", "oz21", "oz22", "oz23", "oz24", "oz25" ]
[ false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false ]
553
211,739
predictive_accuracy
accuracy_score
tr45.wc
null
{0: [0 - sunni (numeric)], 1: [1 - interbank (numeric)], 2: [2 - rig (numeric)], 3: [3 - dlouhi (numeric)], 4: [4 - bratislava (numeric)], 5: [5 - librari (numeric)], 6: [6 - number (numeric)], 7: [7 - contamin (numeric)], 8: [8 - mold (numeric)], 9: [9 - norm (numeric)], 10: [10 - mobil (numeric)], 11: [11 ...
{'MajorityClassSize': 160.0, 'MaxNominalAttDistinctValues': 10.0, 'MinorityClassSize': 14.0, 'NumberOfClasses': 10.0, 'NumberOfFeatures': 8262.0, 'NumberOfInstances': 690.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 8261.0, 'NumberOfSymbolicFeatures': 1...
tr45.wc
[ "sunni", "interbank", "rig", "dlouhi", "bratislava", "librari", "number", "contamin", "mold", "norm", "mobil", "sens", "plankton", "ash", "workstat", "cabin", "sunken", "tengiz", "cove", "tragedi", "alloi", "fluid", "escort", "allot", "curi", "tac", "komsomolet", ...
[ false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, f...
554
5,194
mean_absolute_error
mean_absolute_error
bank8FM
**Author**: **Source**: Unknown - Date unknown **Please cite**: A family of datasets synthetically generated from a simulation of how bank-customers choose their banks. Tasks are based on predicting the fraction of bank customers who leave the bank because of full queues. The bank family of datasets are genera...
{0: [0 - a1cx (numeric)], 1: [1 - a1cy (numeric)], 2: [2 - b2x (numeric)], 3: [3 - b2y (numeric)], 4: [4 - a2pop (numeric)], 5: [5 - a3pop (numeric)], 6: [6 - temp (numeric)], 7: [7 - mxql (numeric)], 8: [8 - rej (numeric)]}
{'MajorityClassSize': nan, 'MaxNominalAttDistinctValues': nan, 'MinorityClassSize': nan, 'NumberOfClasses': 0.0, 'NumberOfFeatures': 9.0, 'NumberOfInstances': 8192.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 9.0, 'NumberOfSymbolicFeatures': 0.0, 'cost...
bank8FM
[ "a1cx", "a1cy", "b2x", "b2y", "a2pop", "a3pop", "temp", "mxql" ]
[ false, false, false, false, false, false, false, false ]
555
5,211
mean_absolute_error
mean_absolute_error
fri_c2_1000_25
**Author**: **Source**: Unknown - Date unknown **Please cite**: The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as "fri_colinearintydegree_samplenumber_featurenumber". Friedman is the one of the most...
{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': 26.0, 'NumberOfInstances': 1000.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 26.0, 'NumberOfSymbolicFeatures': 0.0, 'co...
fri_c2_1000_25
[ "oz1", "oz2", "oz3", "oz4", "oz5", "oz6", "oz7", "oz8", "oz9", "oz10", "oz11", "oz12", "oz13", "oz14", "oz15", "oz16", "oz17", "oz18", "oz19", "oz20", "oz21", "oz22", "oz23", "oz24", "oz25" ]
[ false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false ]
556
211,744
predictive_accuracy
accuracy_score
tr23.wc
null
{0: [0 - utmost (numeric)], 1: [1 - secondli (numeric)], 2: [2 - neglect (numeric)], 3: [3 - shalala (numeric)], 4: [4 - weekend (numeric)], 5: [5 - timefram (numeric)], 6: [6 - formul (numeric)], 7: [7 - lump (numeric)], 8: [8 - belt (numeric)], 9: [9 - cranston (numeric)], 10: [10 - sympathi (numeric)], 11...
{'MajorityClassSize': 91.0, 'MaxNominalAttDistinctValues': 6.0, 'MinorityClassSize': 6.0, 'NumberOfClasses': 6.0, 'NumberOfFeatures': 5833.0, 'NumberOfInstances': 204.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 5832.0, 'NumberOfSymbolicFeatures': 1.0, ...
tr23.wc
[ "utmost", "secondli", "neglect", "shalala", "weekend", "timefram", "formul", "lump", "belt", "cranston", "sympathi", "wrap", "lectur", "underfund", "embargo", "glad", "glar", "multifamili", "perkin", "messr", "demean", "cop", "depart", "multiyear", "blue", "romero",...
[ false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, f...
557
5,206
mean_absolute_error
mean_absolute_error
fri_c4_500_25
**Author**: **Source**: Unknown - Date unknown **Please cite**: The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as "fri_colinearintydegree_samplenumber_featurenumber". Friedman is the one of the most...
{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': 26.0, 'NumberOfInstances': 500.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 26.0, 'NumberOfSymbolicFeatures': 0.0, 'cos...
fri_c4_500_25
[ "oz1", "oz2", "oz3", "oz4", "oz5", "oz6", "oz7", "oz8", "oz9", "oz10", "oz11", "oz12", "oz13", "oz14", "oz15", "oz16", "oz17", "oz18", "oz19", "oz20", "oz21", "oz22", "oz23", "oz24", "oz25" ]
[ false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false ]
558
211,746
predictive_accuracy
accuracy_score
oh0.wc
null
{0: [0 - depart (numeric)], 1: [1 - cluster (numeric)], 2: [2 - nephropathi (numeric)], 3: [3 - sudden (numeric)], 4: [4 - infus (numeric)], 5: [5 - gland (numeric)], 6: [6 - dopamin (numeric)], 7: [7 - fetal (numeric)], 8: [8 - signific (numeric)], 9: [9 - penetr (numeric)], 10: [10 - hepat (numeric)], 11: ...
{'MajorityClassSize': 194.0, 'MaxNominalAttDistinctValues': 10.0, 'MinorityClassSize': 51.0, 'NumberOfClasses': 10.0, 'NumberOfFeatures': 3183.0, 'NumberOfInstances': 1003.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 3182.0, 'NumberOfSymbolicFeatures': ...
oh0.wc
[ "depart", "cluster", "nephropathi", "sudden", "infus", "gland", "dopamin", "fetal", "signific", "penetr", "hepat", "cigarett", "fairli", "resist", "agenc", "rest", "seropreval", "goal", "nucleotid", "hydroxi", "echocardiographi", "decision", "agent", "0", "tongue", ...
[ false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, f...
559
5,205
mean_absolute_error
mean_absolute_error
fri_c1_1000_50
**Author**: **Source**: Unknown - Date unknown **Please cite**: The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as "fri_colinearintydegree_samplenumber_featurenumber". Friedman is the one of the most...
{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': 51.0, 'NumberOfInstances': 1000.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 51.0, 'NumberOfSymbolicFeatures': 0.0, 'co...
fri_c1_1000_50
[ "oz1", "oz2", "oz3", "oz4", "oz5", "oz6", "oz7", "oz8", "oz9", "oz10", "oz11", "oz12", "oz13", "oz14", "oz15", "oz16", "oz17", "oz18", "oz19", "oz20", "oz21", "oz22", "oz23", "oz24", "oz25", "oz26", "oz27", "oz28", "oz29", "oz30", "oz31", "oz32", "oz33...
[ false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, f...
560
4,790
mean_absolute_error
mean_absolute_error
yprop_4_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': 252.0, 'NumberOfInstances': 8885.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 252.0, 'NumberOfSymbolicFeatures': 0.0, '...
yprop_4_1
[ "oz1", "oz2", "oz3", "oz4", "oz5", "oz6", "oz7", "oz8", "oz9", "oz10", "oz11", "oz12", "oz13", "oz14", "oz15", "oz16", "oz17", "oz18", "oz19", "oz20", "oz21", "oz22", "oz23", "oz24", "oz25", "oz26", "oz27", "oz28", "oz29", "oz30", "oz31", "oz32", "oz33...
[ false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, f...
561
5,215
mean_absolute_error
mean_absolute_error
fri_c1_1000_10
**Author**: **Source**: Unknown - Date unknown **Please cite**: The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as "fri_colinearintydegree_samplenumber_featurenumber". Friedman is the one of the most...
{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)]}
{'MajorityClassSize': nan, 'MaxNominalAttDistinctValues': nan, 'MinorityClassSize': nan, 'NumberOfClasses': 0.0, 'NumberOfFeatures': 11.0, 'NumberOfInstances': 1000.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 11.0, 'NumberOfSymbolicFeatures': 0.0, 'co...
fri_c1_1000_10
[ "oz1", "oz2", "oz3", "oz4", "oz5", "oz6", "oz7", "oz8", "oz9", "oz10" ]
[ false, false, false, false, false, false, false, false, false, false ]
562
211,748
predictive_accuracy
accuracy_score
oh5.wc
**Author**: [George Forman](https://scholar.google.com/citations?user=r0a222QAAAAJ) **Source**: http://tunedit.org/repo/Data/Text-wc/oh5.wc.arff **Please cite**:
{0: [0 - depart (numeric)], 1: [1 - nephropathi (numeric)], 2: [2 - cluster (numeric)], 3: [3 - tenth (numeric)], 4: [4 - sudden (numeric)], 5: [5 - infus (numeric)], 6: [6 - imbal (numeric)], 7: [7 - gland (numeric)], 8: [8 - cyclophosphamid (numeric)], 9: [9 - furth (numeric)], 10: [10 - phagocytosi (numeri...
{'MajorityClassSize': 149.0, 'MaxNominalAttDistinctValues': 10.0, 'MinorityClassSize': 59.0, 'NumberOfClasses': 10.0, 'NumberOfFeatures': 3013.0, 'NumberOfInstances': 918.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 3012.0, 'NumberOfSymbolicFeatures': 1...
oh5.wc
[ "depart", "nephropathi", "cluster", "tenth", "sudden", "infus", "imbal", "gland", "cyclophosphamid", "furth", "phagocytosi", "fetal", "signific", "penetr", "hepat", "cigarett", "fusion", "resist", "rest", "goal", "hypothyroid", "posttraumat", "hydroxi", "echocardiograph...
[ false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, f...
563
5,189
mean_absolute_error
mean_absolute_error
water-treatment
**Author**: **Source**: Unknown - Date unknown **Please cite**: 1. Title: Faults in a urban waste water treatment plant 2. Source Information: -- Creators: Manel Poch (igte2@cc.uab.es) Unitat d'Enginyeria Quimica Universitat Autonoma de Barcelona. Bellaterra. Barcelona; Spain -- Donor: Javier Bejar and Ulises...
{0: [0 - date (nominal)], 1: [1 - Q-E (nominal)], 2: [2 - ZN-E (numeric)], 3: [3 - PH-E (numeric)], 4: [4 - DBO-E (nominal)], 5: [5 - DQO-E (nominal)], 6: [6 - SS-E (nominal)], 7: [7 - SSV-E (numeric)], 8: [8 - SED-E (numeric)], 9: [9 - COND-E (nominal)], 10: [10 - PH-P (numeric)], 11: [11 - DBO-P (nominal)]...
{'MajorityClassSize': nan, 'MaxNominalAttDistinctValues': 414.0, 'MinorityClassSize': nan, 'NumberOfClasses': 0.0, 'NumberOfFeatures': 37.0, 'NumberOfInstances': 527.0, 'NumberOfInstancesWithMissingValues': 130.0, 'NumberOfMissingValues': 573.0, 'NumberOfNumericFeatures': 22.0, 'NumberOfSymbolicFeatures': 15.0...
water-treatment
[ "ZN-E", "PH-E", "DBO-E", "DQO-E", "SS-E", "SSV-E", "SED-E", "COND-E", "PH-P", "DBO-P", "SS-P", "SSV-P", "SED-P", "COND-P", "PH-D", "DBO-D", "DQO-D", "SS-D", "SSV-D", "SED-D", "COND-D", "PH-S", "DBO-S", "DQO-S", "SS-S", "SSV-S", "SED-S", "COND-S", "RD-DBO-P", ...
[ false, false, true, true, true, false, false, true, false, true, true, false, false, true, false, true, true, true, false, false, true, false, true, true, true, false, false, true, false, false, false, false, false, false, false, false ]
564
5,217
mean_absolute_error
mean_absolute_error
fri_c0_1000_10
**Author**: **Source**: Unknown - Date unknown **Please cite**: The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as "fri_colinearintydegree_samplenumber_featurenumber". Friedman is the one of the most...
{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)]}
{'MajorityClassSize': nan, 'MaxNominalAttDistinctValues': nan, 'MinorityClassSize': nan, 'NumberOfClasses': 0.0, 'NumberOfFeatures': 11.0, 'NumberOfInstances': 1000.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 11.0, 'NumberOfSymbolicFeatures': 0.0, 'co...
fri_c0_1000_10
[ "oz1", "oz2", "oz3", "oz4", "oz5", "oz6", "oz7", "oz8", "oz9", "oz10" ]
[ false, false, false, false, false, false, false, false, false, false ]
565
5,214
mean_absolute_error
mean_absolute_error
fri_c4_1000_25
**Author**: **Source**: Unknown - Date unknown **Please cite**: The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as "fri_colinearintydegree_samplenumber_featurenumber". Friedman is the one of the most...
{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': 26.0, 'NumberOfInstances': 1000.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 26.0, 'NumberOfSymbolicFeatures': 0.0, 'co...
fri_c4_1000_25
[ "oz1", "oz2", "oz3", "oz4", "oz5", "oz6", "oz7", "oz8", "oz9", "oz10", "oz11", "oz12", "oz13", "oz14", "oz15", "oz16", "oz17", "oz18", "oz19", "oz20", "oz21", "oz22", "oz23", "oz24", "oz25" ]
[ false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false ]
566
5,184
mean_absolute_error
mean_absolute_error
bank32nh
**Author**: **Source**: Unknown - Date unknown **Please cite**: A family of datasets synthetically generated from a simulation of how bank-customers choose their banks. Tasks are based on predicting the fraction of bank customers who leave the bank because of full queues. The bank family of datasets are genera...
{0: [0 - a1cx (numeric)], 1: [1 - a1cy (numeric)], 2: [2 - a1sx (numeric)], 3: [3 - a1sy (numeric)], 4: [4 - a1rho (numeric)], 5: [5 - a1pop (numeric)], 6: [6 - a2cx (numeric)], 7: [7 - a2cy (numeric)], 8: [8 - a2sx (numeric)], 9: [9 - a2sy (numeric)], 10: [10 - a2rho (numeric)], 11: [11 - a2pop (numeric)], ...
{'MajorityClassSize': nan, 'MaxNominalAttDistinctValues': nan, 'MinorityClassSize': nan, 'NumberOfClasses': 0.0, 'NumberOfFeatures': 33.0, 'NumberOfInstances': 8192.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 33.0, 'NumberOfSymbolicFeatures': 0.0, 'co...
bank32nh
[ "a1cx", "a1cy", "a1sx", "a1sy", "a1rho", "a1pop", "a2cx", "a2cy", "a2sx", "a2sy", "a2rho", "a2pop", "a3cx", "a3cy", "a3sx", "a3sy", "a3rho", "a3pop", "temp", "b1x", "b1y", "b1call", "b1eff", "b2x", "b2y", "b2call", "b2eff", "b3x", "b3y", "b3call", "b3eff",...
[ false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false ]
567
5,195
mean_absolute_error
mean_absolute_error
cpu_act
**Author**: **Source**: Unknown - Date unknown **Please cite**: The Computer Activity databases are a collection of computer systems activity measures. The data was collected from a Sun Sparcstation 20/712 with 128 Mbytes of memory running in a multi-user university department. Users would typically be doing a...
{0: [0 - lread (numeric)], 1: [1 - lwrite (numeric)], 2: [2 - scall (numeric)], 3: [3 - sread (numeric)], 4: [4 - swrite (numeric)], 5: [5 - fork (numeric)], 6: [6 - exec (numeric)], 7: [7 - rchar (numeric)], 8: [8 - wchar (numeric)], 9: [9 - pgout (numeric)], 10: [10 - ppgout (numeric)], 11: [11 - pgfree (n...
{'MajorityClassSize': nan, 'MaxNominalAttDistinctValues': nan, 'MinorityClassSize': nan, 'NumberOfClasses': 0.0, 'NumberOfFeatures': 22.0, 'NumberOfInstances': 8192.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 22.0, 'NumberOfSymbolicFeatures': 0.0, 'co...
cpu_act
[ "lread", "lwrite", "scall", "sread", "swrite", "fork", "exec", "rchar", "wchar", "pgout", "ppgout", "pgfree", "pgscan", "atch", "pgin", "ppgin", "pflt", "vflt", "runqsz", "freemem", "freeswap" ]
[ false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false ]
568
5,224
mean_absolute_error
mean_absolute_error
fri_c3_250_10
**Author**: **Source**: Unknown - Date unknown **Please cite**: The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as "fri_colinearintydegree_samplenumber_featurenumber". Friedman is the one of the most...
{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)]}
{'MajorityClassSize': nan, 'MaxNominalAttDistinctValues': nan, 'MinorityClassSize': nan, 'NumberOfClasses': 0.0, 'NumberOfFeatures': 11.0, 'NumberOfInstances': 250.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 11.0, 'NumberOfSymbolicFeatures': 0.0, 'cos...
fri_c3_250_10
[ "oz1", "oz2", "oz3", "oz4", "oz5", "oz6", "oz7", "oz8", "oz9", "oz10" ]
[ false, false, false, false, false, false, false, false, false, false ]
569
211,740
predictive_accuracy
accuracy_score
tr21.wc
null
{0: [0 - noteworthi (numeric)], 1: [1 - parad (numeric)], 2: [2 - naval (numeric)], 3: [3 - ward (numeric)], 4: [4 - dock (numeric)], 5: [5 - logist (numeric)], 6: [6 - tonnag (numeric)], 7: [7 - maine (numeric)], 8: [8 - ap (numeric)], 9: [9 - sallie (numeric)], 10: [10 - franci (numeric)], 11: [11 - libert...
{'MajorityClassSize': 231.0, 'MaxNominalAttDistinctValues': 6.0, 'MinorityClassSize': 4.0, 'NumberOfClasses': 6.0, 'NumberOfFeatures': 7903.0, 'NumberOfInstances': 336.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 7902.0, 'NumberOfSymbolicFeatures': 1.0,...
tr21.wc
[ "noteworthi", "parad", "naval", "ward", "dock", "logist", "tonnag", "maine", "ap", "sallie", "franci", "libertarian", "pip", "russell", "sanford", "approp", "ind", "shipboard", "sunset", "servant", "depart", "logansport", "number", "english", "maritim", "signific", ...
[ false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, f...
570
5,216
mean_absolute_error
mean_absolute_error
fri_c2_100_5
**Author**: **Source**: Unknown - Date unknown **Please cite**: The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as "fri_colinearintydegree_samplenumber_featurenumber". Friedman is the one of the most...
{0: [0 - oz1 (numeric)], 1: [1 - oz2 (numeric)], 2: [2 - oz3 (numeric)], 3: [3 - oz4 (numeric)], 4: [4 - oz5 (numeric)], 5: [5 - oz6 (numeric)]}
{'MajorityClassSize': nan, 'MaxNominalAttDistinctValues': nan, 'MinorityClassSize': nan, 'NumberOfClasses': 0.0, 'NumberOfFeatures': 6.0, 'NumberOfInstances': 100.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 6.0, 'NumberOfSymbolicFeatures': 0.0, 'cost_...
fri_c2_100_5
[ "oz1", "oz2", "oz3", "oz4", "oz5" ]
[ false, false, false, false, false ]
571
211,743
predictive_accuracy
accuracy_score
tr11.wc
null
{0: [0 - outfit (numeric)], 1: [1 - hasn (numeric)], 2: [2 - calm (numeric)], 3: [3 - gene (numeric)], 4: [4 - resettl (numeric)], 5: [5 - lotteri (numeric)], 6: [6 - privileg (numeric)], 7: [7 - junior (numeric)], 8: [8 - withdrawn (numeric)], 9: [9 - chok (numeric)], 10: [10 - compaq (numeric)], 11: [11 - ...
{'MajorityClassSize': 132.0, 'MaxNominalAttDistinctValues': 9.0, 'MinorityClassSize': 6.0, 'NumberOfClasses': 9.0, 'NumberOfFeatures': 6430.0, 'NumberOfInstances': 414.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 6429.0, 'NumberOfSymbolicFeatures': 1.0,...
tr11.wc
[ "outfit", "hasn", "calm", "gene", "resettl", "lotteri", "privileg", "junior", "withdrawn", "chok", "compaq", "noi", "colombia", "radioact", "neutron", "npc", "disabl", "macedonian", "eman", "skopje", "volkov", "appall", "sidelin", "titanium", "quasi", "league", "n...
[ false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, f...
572
211,755
predictive_accuracy
accuracy_score
oh10.wc
null
{0: [0 - sudden (numeric)], 1: [1 - gland (numeric)], 2: [2 - signific (numeric)], 3: [3 - penetr (numeric)], 4: [4 - hepat (numeric)], 5: [5 - fusion (numeric)], 6: [6 - agenc (numeric)], 7: [7 - rest (numeric)], 8: [8 - seropreval (numeric)], 9: [9 - nucleotid (numeric)], 10: [10 - echocardiographi (numeric...
{'MajorityClassSize': 165.0, 'MaxNominalAttDistinctValues': 10.0, 'MinorityClassSize': 52.0, 'NumberOfClasses': 10.0, 'NumberOfFeatures': 3239.0, 'NumberOfInstances': 1050.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 3238.0, 'NumberOfSymbolicFeatures': ...
oh10.wc
[ "sudden", "gland", "signific", "penetr", "hepat", "fusion", "agenc", "rest", "seropreval", "nucleotid", "echocardiographi", "decision", "agent", "0", "placem", "environ", "obstetr", "vagin", "overview", "cytokin", "reconstitut", "discharg", "f", "ileal", "g", "clind...
[ false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, f...
573
211,741
predictive_accuracy
accuracy_score
tr31.wc
null
{0: [0 - cone (numeric)], 1: [1 - protection (numeric)], 2: [2 - wir (numeric)], 3: [3 - fright (numeric)], 4: [4 - resold (numeric)], 5: [5 - thirsti (numeric)], 6: [6 - isolina (numeric)], 7: [7 - lucho (numeric)], 8: [8 - wari (numeric)], 9: [9 - sermon (numeric)], 10: [10 - unwis (numeric)], 11: [11 - co...
{'MajorityClassSize': 352.0, 'MaxNominalAttDistinctValues': 7.0, 'MinorityClassSize': 2.0, 'NumberOfClasses': 7.0, 'NumberOfFeatures': 10129.0, 'NumberOfInstances': 927.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 10128.0, 'NumberOfSymbolicFeatures': 1....
tr31.wc
[ "cone", "protection", "wir", "fright", "resold", "thirsti", "isolina", "lucho", "wari", "sermon", "unwis", "commenc", "optic", "ah", "reservoir", "au", "uninjur", "deflat", "enclav", "narcodollar", "delgado", "jakarta", "oxapampa", "yonsei", "modul", "labell", "in...
[ false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, f...
574
211,751
predictive_accuracy
accuracy_score
tr12.wc
null
{0: [0 - saga (numeric)], 1: [1 - stumble (numeric)], 2: [2 - abu (numeric)], 3: [3 - membership (numeric)], 4: [4 - rc (numeric)], 5: [5 - cherish (numeric)], 6: [6 - airwai (numeric)], 7: [7 - concur (numeric)], 8: [8 - ravag (numeric)], 9: [9 - perestroyka (numeric)], 10: [10 - rf (numeric)], 11: [11 - 0 ...
{'MajorityClassSize': 93.0, 'MaxNominalAttDistinctValues': 8.0, 'MinorityClassSize': 9.0, 'NumberOfClasses': 8.0, 'NumberOfFeatures': 5805.0, 'NumberOfInstances': 313.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 5804.0, 'NumberOfSymbolicFeatures': 1.0, ...
tr12.wc
[ "saga", "stumble", "abu", "membership", "rc", "cherish", "airwai", "concur", "ravag", "perestroyka", "rf", "0", "environ", "purchas", "loss", "lost", "manag", "particip", "southeast", "product", "dinner", "anglo", "aqueou", "deton", "conspiraci", "ethic", "criteri...
[ false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, f...
575
5,212
mean_absolute_error
mean_absolute_error
fri_c0_1000_50
**Author**: **Source**: Unknown - Date unknown **Please cite**: The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as "fri_colinearintydegree_samplenumber_featurenumber". Friedman is the one of the most...
{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': 51.0, 'NumberOfInstances': 1000.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 51.0, 'NumberOfSymbolicFeatures': 0.0, 'co...
fri_c0_1000_50
[ "oz1", "oz2", "oz3", "oz4", "oz5", "oz6", "oz7", "oz8", "oz9", "oz10", "oz11", "oz12", "oz13", "oz14", "oz15", "oz16", "oz17", "oz18", "oz19", "oz20", "oz21", "oz22", "oz23", "oz24", "oz25", "oz26", "oz27", "oz28", "oz29", "oz30", "oz31", "oz32", "oz33...
[ false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, f...
576
211,749
predictive_accuracy
accuracy_score
re1.wc
null
{0: [0 - imbal (numeric)], 1: [1 - subsidis (numeric)], 2: [2 - signific (numeric)], 3: [3 - fairli (numeric)], 4: [4 - rest (numeric)], 5: [5 - agenc (numeric)], 6: [6 - violent (numeric)], 7: [7 - francais (numeric)], 8: [8 - chuck (numeric)], 9: [9 - decision (numeric)], 10: [10 - agent (numeric)], 11: [1...
{'MajorityClassSize': 371.0, 'MaxNominalAttDistinctValues': 25.0, 'MinorityClassSize': 10.0, 'NumberOfClasses': 25.0, 'NumberOfFeatures': 3759.0, 'NumberOfInstances': 1657.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 3758.0, 'NumberOfSymbolicFeatures': ...
re1.wc
[ "imbal", "subsidis", "signific", "fairli", "rest", "agenc", "violent", "francais", "chuck", "decision", "agent", "0", "tower", "margarin", "placem", "curtail", "placer", "environ", "hamburg", "und", "fly", "panamanian", "housew", "pension", "discharg", "e", "drake...
[ false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, f...
577
5,221
mean_absolute_error
mean_absolute_error
fri_c2_1000_5
**Author**: **Source**: Unknown - Date unknown **Please cite**: The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as "fri_colinearintydegree_samplenumber_featurenumber". Friedman is the one of the most...
{0: [0 - oz1 (numeric)], 1: [1 - oz2 (numeric)], 2: [2 - oz3 (numeric)], 3: [3 - oz4 (numeric)], 4: [4 - oz5 (numeric)], 5: [5 - oz6 (numeric)]}
{'MajorityClassSize': nan, 'MaxNominalAttDistinctValues': nan, 'MinorityClassSize': nan, 'NumberOfClasses': 0.0, 'NumberOfFeatures': 6.0, 'NumberOfInstances': 1000.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 6.0, 'NumberOfSymbolicFeatures': 0.0, 'cost...
fri_c2_1000_5
[ "oz1", "oz2", "oz3", "oz4", "oz5" ]
[ false, false, false, false, false ]
578
211,788
predictive_accuracy
accuracy_score
heart
**Author**: Laboratory of Artificial Intelligence and Computer Science of the University of Porto (LIACC) libSVM","AAD group **Source**: [original](http://www.csie.ntu.edu.tw/~cjlin/libsvmtools/datasets/binary.html) - Date unknown **Please cite**: #Dataset from the LIBSVM data repository. Preprocessing: scal...
{0: [0 - att_1 (numeric)], 1: [1 - att_2 (numeric)], 2: [2 - att_3 (numeric)], 3: [3 - att_4 (numeric)], 4: [4 - att_5 (numeric)], 5: [5 - att_6 (numeric)], 6: [6 - att_7 (numeric)], 7: [7 - att_8 (numeric)], 8: [8 - att_9 (numeric)], 9: [9 - att_10 (numeric)], 10: [10 - att_11 (numeric)], 11: [11 - att_12 (...
{'MajorityClassSize': nan, 'MaxNominalAttDistinctValues': nan, 'MinorityClassSize': nan, 'NumberOfClasses': 0.0, 'NumberOfFeatures': 14.0, 'NumberOfInstances': 270.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 14.0, 'NumberOfSymbolicFeatures': 0.0, 'cos...
heart
[ "att_1", "att_2", "att_3", "att_4", "att_5", "att_6", "att_7", "att_8", "att_9", "att_10", "att_11", "att_12", "att_13" ]
[ false, false, false, false, false, false, false, false, false, false, false, false, false ]
579
5,219
mean_absolute_error
mean_absolute_error
fri_c2_500_5
**Author**: **Source**: Unknown - Date unknown **Please cite**: The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as "fri_colinearintydegree_samplenumber_featurenumber". Friedman is the one of the most...
{0: [0 - oz1 (numeric)], 1: [1 - oz2 (numeric)], 2: [2 - oz3 (numeric)], 3: [3 - oz4 (numeric)], 4: [4 - oz5 (numeric)], 5: [5 - oz6 (numeric)]}
{'MajorityClassSize': nan, 'MaxNominalAttDistinctValues': nan, 'MinorityClassSize': nan, 'NumberOfClasses': 0.0, 'NumberOfFeatures': 6.0, 'NumberOfInstances': 500.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 6.0, 'NumberOfSymbolicFeatures': 0.0, 'cost_...
fri_c2_500_5
[ "oz1", "oz2", "oz3", "oz4", "oz5" ]
[ false, false, false, false, false ]
580
211,784
predictive_accuracy
accuracy_score
german.numer
null
{0: [0 - att_1 (numeric)], 1: [1 - att_2 (numeric)], 2: [2 - att_3 (numeric)], 3: [3 - att_4 (numeric)], 4: [4 - att_5 (numeric)], 5: [5 - att_6 (numeric)], 6: [6 - att_7 (numeric)], 7: [7 - att_8 (numeric)], 8: [8 - att_9 (numeric)], 9: [9 - att_10 (numeric)], 10: [10 - att_11 (numeric)], 11: [11 - att_12 (...
{'MajorityClassSize': nan, 'MaxNominalAttDistinctValues': nan, 'MinorityClassSize': nan, 'NumberOfClasses': 0.0, 'NumberOfFeatures': 25.0, 'NumberOfInstances': 1000.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 25.0, 'NumberOfSymbolicFeatures': 0.0, 'co...
german.numer
[ "att_1", "att_2", "att_3", "att_4", "att_5", "att_6", "att_7", "att_8", "att_9", "att_10", "att_11", "att_12", "att_13", "att_14", "att_15", "att_16", "att_17", "att_18", "att_19", "att_20", "att_21", "att_22", "att_23", "att_24" ]
[ false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false ]
581
211,783
predictive_accuracy
accuracy_score
fourclass
**Author**: Tin Kam Ho and Eugene M. Kleinberg. **Source**: [original](http://www.csie.ntu.edu.tw/~cjlin/libsvmtools/datasets/binary.html) - Date unknown **Please cite**: Tin Kam Ho and Eugene M. Kleinberg. Building projectable classifiers of arbitrary complexity. In Proceedings of the 13th International Conference...
{0: [0 - att_1 (numeric)], 1: [1 - att_2 (numeric)], 2: [2 - class (numeric)]}
{'MajorityClassSize': nan, 'MaxNominalAttDistinctValues': nan, 'MinorityClassSize': nan, 'NumberOfClasses': 0.0, 'NumberOfFeatures': 3.0, 'NumberOfInstances': 862.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 3.0, 'NumberOfSymbolicFeatures': 0.0, 'cost_...
fourclass
[ "att_1", "att_2" ]
[ false, false ]
582
211,781
predictive_accuracy
accuracy_score
svmguide1
**Author**: Chih-Wei Hsu","Chih-Chung Chang","and Chih-Jen Lin. libSVM","AAD group **Source**: [original](http://www.csie.ntu.edu.tw/~cjlin/libsvmtools/datasets/binary.html) - Date unknown **Please cite**: Chih-Wei Hsu, Chih-Chung Chang, and Chih-Jen Lin. A practical guide to support vector classification. Techni...
{0: [0 - att_1 (numeric)], 1: [1 - att_2 (numeric)], 2: [2 - att_3 (numeric)], 3: [3 - att_4 (numeric)], 4: [4 - class (numeric)]}
{'MajorityClassSize': nan, 'MaxNominalAttDistinctValues': nan, 'MinorityClassSize': nan, 'NumberOfClasses': 0.0, 'NumberOfFeatures': 5.0, 'NumberOfInstances': 7089.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 5.0, 'NumberOfSymbolicFeatures': 0.0, 'cost...
svmguide1
[ "att_1", "att_2", "att_3", "att_4" ]
[ false, false, false, false ]
583
5,222
mean_absolute_error
mean_absolute_error
fri_c0_100_50
**Author**: **Source**: Unknown - Date unknown **Please cite**: The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as "fri_colinearintydegree_samplenumber_featurenumber". Friedman is the one of the most...
{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': 51.0, 'NumberOfInstances': 100.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 51.0, 'NumberOfSymbolicFeatures': 0.0, 'cos...
fri_c0_100_50
[ "oz1", "oz2", "oz3", "oz4", "oz5", "oz6", "oz7", "oz8", "oz9", "oz10", "oz11", "oz12", "oz13", "oz14", "oz15", "oz16", "oz17", "oz18", "oz19", "oz20", "oz21", "oz22", "oz23", "oz24", "oz25", "oz26", "oz27", "oz28", "oz29", "oz30", "oz31", "oz32", "oz33...
[ false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, f...
584
211,786
predictive_accuracy
accuracy_score
german.numer
null
{0: [0 - att_1 (numeric)], 1: [1 - att_2 (numeric)], 2: [2 - att_3 (numeric)], 3: [3 - att_4 (numeric)], 4: [4 - att_5 (numeric)], 5: [5 - att_6 (numeric)], 6: [6 - att_7 (numeric)], 7: [7 - att_8 (numeric)], 8: [8 - att_9 (numeric)], 9: [9 - att_10 (numeric)], 10: [10 - att_11 (numeric)], 11: [11 - att_12 (...
{'MajorityClassSize': nan, 'MaxNominalAttDistinctValues': nan, 'MinorityClassSize': nan, 'NumberOfClasses': 0.0, 'NumberOfFeatures': 25.0, 'NumberOfInstances': 1000.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 25.0, 'NumberOfSymbolicFeatures': 0.0, 'co...
german.numer
[ "att_1", "att_2", "att_3", "att_4", "att_5", "att_6", "att_7", "att_8", "att_9", "att_10", "att_11", "att_12", "att_13", "att_14", "att_15", "att_16", "att_17", "att_18", "att_19", "att_20", "att_21", "att_22", "att_23", "att_24" ]
[ false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false ]
585
211,785
predictive_accuracy
accuracy_score
fourclass_scale
**Author**: Tin Kam Ho and Eugene M. Kleinberg. libSVM","AAD group **Source**: [original](http://www.csie.ntu.edu.tw/~cjlin/libsvmtools/datasets/binary.html) - Date unknown **Please cite**: #Dataset from the LIBSVM data repository. Preprocessing: transform to two-class
{0: [0 - att_1 (numeric)], 1: [1 - att_2 (numeric)], 2: [2 - class (numeric)]}
{'MajorityClassSize': nan, 'MaxNominalAttDistinctValues': nan, 'MinorityClassSize': nan, 'NumberOfClasses': 0.0, 'NumberOfFeatures': 3.0, 'NumberOfInstances': 862.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 3.0, 'NumberOfSymbolicFeatures': 0.0, 'cost_...
fourclass_scale
[ "att_1", "att_2" ]
[ false, false ]
586
5,226
mean_absolute_error
mean_absolute_error
fri_c4_500_10
**Author**: **Source**: Unknown - Date unknown **Please cite**: The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as "fri_colinearintydegree_samplenumber_featurenumber". Friedman is the one of the most...
{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)]}
{'MajorityClassSize': nan, 'MaxNominalAttDistinctValues': nan, 'MinorityClassSize': nan, 'NumberOfClasses': 0.0, 'NumberOfFeatures': 11.0, 'NumberOfInstances': 500.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 11.0, 'NumberOfSymbolicFeatures': 0.0, 'cos...
fri_c4_500_10
[ "oz1", "oz2", "oz3", "oz4", "oz5", "oz6", "oz7", "oz8", "oz9", "oz10" ]
[ false, false, false, false, false, false, false, false, false, false ]
587
5,230
mean_absolute_error
mean_absolute_error
fri_c3_1000_10
**Author**: **Source**: Unknown - Date unknown **Please cite**: The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as "fri_colinearintydegree_samplenumber_featurenumber". Friedman is the one of the most...
{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)]}
{'MajorityClassSize': nan, 'MaxNominalAttDistinctValues': nan, 'MinorityClassSize': nan, 'NumberOfClasses': 0.0, 'NumberOfFeatures': 11.0, 'NumberOfInstances': 1000.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 11.0, 'NumberOfSymbolicFeatures': 0.0, 'co...
fri_c3_1000_10
[ "oz1", "oz2", "oz3", "oz4", "oz5", "oz6", "oz7", "oz8", "oz9", "oz10" ]
[ false, false, false, false, false, false, false, false, false, false ]
588
5,223
mean_absolute_error
mean_absolute_error
fri_c1_250_5
**Author**: **Source**: Unknown - Date unknown **Please cite**: The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as "fri_colinearintydegree_samplenumber_featurenumber". Friedman is the one of the most...
{0: [0 - oz1 (numeric)], 1: [1 - oz2 (numeric)], 2: [2 - oz3 (numeric)], 3: [3 - oz4 (numeric)], 4: [4 - oz5 (numeric)], 5: [5 - oz6 (numeric)]}
{'MajorityClassSize': nan, 'MaxNominalAttDistinctValues': nan, 'MinorityClassSize': nan, 'NumberOfClasses': 0.0, 'NumberOfFeatures': 6.0, 'NumberOfInstances': 250.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 6.0, 'NumberOfSymbolicFeatures': 0.0, 'cost_...
fri_c1_250_5
[ "oz1", "oz2", "oz3", "oz4", "oz5" ]
[ false, false, false, false, false ]
590
5,035
mean_absolute_error
mean_absolute_error
Brainsize
**Author**: **Source**: Unknown - Date unknown **Please cite**: Datasets of Data And Story Library, project illustrating use of basic statistic methods, converted to arff format by Hakan Kjellerstrand. Source: TunedIT: http://tunedit.org/repo/DASL DASL file http://lib.stat.cmu.edu/DASL/Datafiles/Brainsize.htm...
{0: [0 - Gender (nominal)], 1: [1 - FSIQ (numeric)], 2: [2 - VIQ (numeric)], 3: [3 - PIQ (numeric)], 4: [4 - Weight (numeric)], 5: [5 - Height (numeric)], 6: [6 - MRI_Count (numeric)]}
{'MajorityClassSize': nan, 'MaxNominalAttDistinctValues': 2.0, 'MinorityClassSize': nan, 'NumberOfClasses': 0.0, 'NumberOfFeatures': 7.0, 'NumberOfInstances': 40.0, 'NumberOfInstancesWithMissingValues': 2.0, 'NumberOfMissingValues': 3.0, 'NumberOfNumericFeatures': 6.0, 'NumberOfSymbolicFeatures': 1.0, 'cost_m...
Brainsize
[ "Gender", "FSIQ", "VIQ", "PIQ", "Weight", "Height" ]
[ true, false, false, false, false, false ]
591
5,232
mean_absolute_error
mean_absolute_error
fri_c4_500_100
**Author**: **Source**: Unknown - Date unknown **Please cite**: The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as "fri_colinearintydegree_samplenumber_featurenumber". Friedman is the one of the most...
{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': 101.0, 'NumberOfInstances': 500.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 101.0, 'NumberOfSymbolicFeatures': 0.0, 'c...
fri_c4_500_100
[ "oz1", "oz2", "oz3", "oz4", "oz5", "oz6", "oz7", "oz8", "oz9", "oz10", "oz11", "oz12", "oz13", "oz14", "oz15", "oz16", "oz17", "oz18", "oz19", "oz20", "oz21", "oz22", "oz23", "oz24", "oz25", "oz26", "oz27", "oz28", "oz29", "oz30", "oz31", "oz32", "oz33...
[ false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, f...
592
211,754
predictive_accuracy
accuracy_score
tr41.wc
null
{0: [0 - lighthous (numeric)], 1: [1 - conquest (numeric)], 2: [2 - algerian (numeric)], 3: [3 - banish (numeric)], 4: [4 - jerri (numeric)], 5: [5 - nationalist (numeric)], 6: [6 - evil (numeric)], 7: [7 - beirut (numeric)], 8: [8 - worrisom (numeric)], 9: [9 - stolen (numeric)], 10: [10 - durabl (numeric)],...
{'MajorityClassSize': 243.0, 'MaxNominalAttDistinctValues': 10.0, 'MinorityClassSize': 9.0, 'NumberOfClasses': 10.0, 'NumberOfFeatures': 7455.0, 'NumberOfInstances': 878.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 7454.0, 'NumberOfSymbolicFeatures': 1....
tr41.wc
[ "lighthous", "conquest", "algerian", "banish", "jerri", "nationalist", "evil", "beirut", "worrisom", "stolen", "durabl", "adburgham", "restart", "lee", "avonmouth", "wive", "exot", "tighter", "tenth", "polic", "diane", "perish", "altimet", "princeton", "eb", "diseas...
[ false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, f...
593
5,218
mean_absolute_error
mean_absolute_error
fri_c2_250_5
**Author**: **Source**: Unknown - Date unknown **Please cite**: The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as "fri_colinearintydegree_samplenumber_featurenumber". Friedman is the one of the most...
{0: [0 - oz1 (numeric)], 1: [1 - oz2 (numeric)], 2: [2 - oz3 (numeric)], 3: [3 - oz4 (numeric)], 4: [4 - oz5 (numeric)], 5: [5 - oz6 (numeric)]}
{'MajorityClassSize': nan, 'MaxNominalAttDistinctValues': nan, 'MinorityClassSize': nan, 'NumberOfClasses': 0.0, 'NumberOfFeatures': 6.0, 'NumberOfInstances': 250.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 6.0, 'NumberOfSymbolicFeatures': 0.0, 'cost_...
fri_c2_250_5
[ "oz1", "oz2", "oz3", "oz4", "oz5" ]
[ false, false, false, false, false ]
594
5,225
mean_absolute_error
mean_absolute_error
fri_c0_250_50
**Author**: **Source**: Unknown - Date unknown **Please cite**: The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as "fri_colinearintydegree_samplenumber_featurenumber". Friedman is the one of the most...
{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': 51.0, 'NumberOfInstances': 250.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 51.0, 'NumberOfSymbolicFeatures': 0.0, 'cos...
fri_c0_250_50
[ "oz1", "oz2", "oz3", "oz4", "oz5", "oz6", "oz7", "oz8", "oz9", "oz10", "oz11", "oz12", "oz13", "oz14", "oz15", "oz16", "oz17", "oz18", "oz19", "oz20", "oz21", "oz22", "oz23", "oz24", "oz25", "oz26", "oz27", "oz28", "oz29", "oz30", "oz31", "oz32", "oz33...
[ false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, f...
595
211,801
predictive_accuracy
accuracy_score
svmguide3
**Author**: Chih-Wei Hsu","Chih-Chung Chang","and Chih-Jen Lin. libSVM","AAD group **Source**: [original](http://www.csie.ntu.edu.tw/~cjlin/libsvmtools/datasets/binary.html) - Date unknown **Please cite**: #Dataset from the LIBSVM data repository. Preprocessing: Original data: someone from Germany working wi...
{0: [0 - att_1 (numeric)], 1: [1 - att_2 (numeric)], 2: [2 - att_3 (numeric)], 3: [3 - att_4 (numeric)], 4: [4 - att_5 (numeric)], 5: [5 - att_6 (numeric)], 6: [6 - att_7 (numeric)], 7: [7 - att_8 (numeric)], 8: [8 - att_9 (numeric)], 9: [9 - att_10 (numeric)], 10: [10 - att_11 (numeric)], 11: [11 - att_12 (...
{'MajorityClassSize': nan, 'MaxNominalAttDistinctValues': nan, 'MinorityClassSize': nan, 'NumberOfClasses': 0.0, 'NumberOfFeatures': 23.0, 'NumberOfInstances': 1243.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 23.0, 'NumberOfSymbolicFeatures': 0.0, 'co...
svmguide3
[ "att_1", "att_2", "att_3", "att_4", "att_5", "att_6", "att_7", "att_8", "att_9", "att_10", "att_11", "att_12", "att_13", "att_14", "att_15", "att_16", "att_17", "att_18", "att_19", "att_20", "att_21", "att_22" ]
[ false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false ]
596
5,220
mean_absolute_error
mean_absolute_error
fri_c0_1000_25
**Author**: **Source**: Unknown - Date unknown **Please cite**: The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as "fri_colinearintydegree_samplenumber_featurenumber". Friedman is the one of the most...
{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': 26.0, 'NumberOfInstances': 1000.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 26.0, 'NumberOfSymbolicFeatures': 0.0, 'co...
fri_c0_1000_25
[ "oz1", "oz2", "oz3", "oz4", "oz5", "oz6", "oz7", "oz8", "oz9", "oz10", "oz11", "oz12", "oz13", "oz14", "oz15", "oz16", "oz17", "oz18", "oz19", "oz20", "oz21", "oz22", "oz23", "oz24", "oz25" ]
[ false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false ]
597
5,236
mean_absolute_error
mean_absolute_error
fri_c1_250_25
**Author**: **Source**: Unknown - Date unknown **Please cite**: The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as "fri_colinearintydegree_samplenumber_featurenumber". Friedman is the one of the most...
{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': 26.0, 'NumberOfInstances': 250.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 26.0, 'NumberOfSymbolicFeatures': 0.0, 'cos...
fri_c1_250_25
[ "oz1", "oz2", "oz3", "oz4", "oz5", "oz6", "oz7", "oz8", "oz9", "oz10", "oz11", "oz12", "oz13", "oz14", "oz15", "oz16", "oz17", "oz18", "oz19", "oz20", "oz21", "oz22", "oz23", "oz24", "oz25" ]
[ false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false ]
598
5,233
mean_absolute_error
mean_absolute_error
fri_c3_100_5
**Author**: **Source**: Unknown - Date unknown **Please cite**: The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as "fri_colinearintydegree_samplenumber_featurenumber". Friedman is the one of the most...
{0: [0 - oz1 (numeric)], 1: [1 - oz2 (numeric)], 2: [2 - oz3 (numeric)], 3: [3 - oz4 (numeric)], 4: [4 - oz5 (numeric)], 5: [5 - oz6 (numeric)]}
{'MajorityClassSize': nan, 'MaxNominalAttDistinctValues': nan, 'MinorityClassSize': nan, 'NumberOfClasses': 0.0, 'NumberOfFeatures': 6.0, 'NumberOfInstances': 100.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 6.0, 'NumberOfSymbolicFeatures': 0.0, 'cost_...
fri_c3_100_5
[ "oz1", "oz2", "oz3", "oz4", "oz5" ]
[ false, false, false, false, false ]
599
5,046
mean_absolute_error
mean_absolute_error
bolts
**Author**: **Source**: Unknown - **Please cite**: Data from StatLib (ftp stat.cmu.edu/datasets) SUMMARY: Data from an experiment on the affects of machine adjustments on the time to count bolts. Data appear as the STATS (Issue 10) Challenge. DATA: Submitted by W. Robert Stephenson, Iowa State U...
{0: [0 - RUN (numeric)], 1: [1 - SPEED1 (numeric)], 2: [2 - TOTAL (numeric)], 3: [3 - SPEED2 (numeric)], 4: [4 - NUMBER2 (numeric)], 5: [5 - SENS (numeric)], 6: [6 - TIME (numeric)], 7: [7 - T20BOLT (numeric)]}
{'MajorityClassSize': nan, 'MaxNominalAttDistinctValues': nan, 'MinorityClassSize': nan, 'NumberOfClasses': 0.0, 'NumberOfFeatures': 7.0, 'NumberOfInstances': 40.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 7.0, 'NumberOfSymbolicFeatures': 0.0, 'cost_m...
bolts
[ "SPEED1", "TOTAL", "SPEED2", "NUMBER2", "SENS", "TIME" ]
[ false, false, false, false, false, false ]
600
5,228
mean_absolute_error
mean_absolute_error
fri_c2_1000_10
**Author**: **Source**: Unknown - Date unknown **Please cite**: The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as "fri_colinearintydegree_samplenumber_featurenumber". Friedman is the one of the most...
{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)]}
{'MajorityClassSize': nan, 'MaxNominalAttDistinctValues': nan, 'MinorityClassSize': nan, 'NumberOfClasses': 0.0, 'NumberOfFeatures': 11.0, 'NumberOfInstances': 1000.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 11.0, 'NumberOfSymbolicFeatures': 0.0, 'co...
fri_c2_1000_10
[ "oz1", "oz2", "oz3", "oz4", "oz5", "oz6", "oz7", "oz8", "oz9", "oz10" ]
[ false, false, false, false, false, false, false, false, false, false ]
601
5,023
mean_absolute_error
mean_absolute_error
LEV
**Author**: **Source**: Unknown - Date unknown **Please cite**: 1. Title: Lecturers Evaluation (Ordinal LEV) 2. Source Informaion: Donor: Arie Ben David MIS, Dept. of Technology Management Holon Academic Inst. of Technology 52 Golomb St. Holon 58102 Israel...
{0: [0 - In1 (numeric)], 1: [1 - In2 (numeric)], 2: [2 - In3 (numeric)], 3: [3 - In4 (numeric)], 4: [4 - Out1 (numeric)]}
{'MajorityClassSize': nan, 'MaxNominalAttDistinctValues': nan, 'MinorityClassSize': nan, 'NumberOfClasses': 0.0, 'NumberOfFeatures': 5.0, 'NumberOfInstances': 1000.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 5.0, 'NumberOfSymbolicFeatures': 0.0, 'cost...
LEV
[ "In1", "In2", "In3", "In4" ]
[ false, false, false, false ]
602
211,843
mean_absolute_error
mean_absolute_error
heart
**Author**: Laboratory of Artificial Intelligence and Computer Science of the University of Porto (LIACC) libSVM","AAD group **Source**: [original](http://www.csie.ntu.edu.tw/~cjlin/libsvmtools/datasets/binary.html) - Date unknown **Please cite**: #Dataset from the LIBSVM data repository. Preprocessing: scal...
{0: [0 - att_1 (numeric)], 1: [1 - att_2 (numeric)], 2: [2 - att_3 (numeric)], 3: [3 - att_4 (numeric)], 4: [4 - att_5 (numeric)], 5: [5 - att_6 (numeric)], 6: [6 - att_7 (numeric)], 7: [7 - att_8 (numeric)], 8: [8 - att_9 (numeric)], 9: [9 - att_10 (numeric)], 10: [10 - att_11 (numeric)], 11: [11 - att_12 (...
{'MajorityClassSize': nan, 'MaxNominalAttDistinctValues': nan, 'MinorityClassSize': nan, 'NumberOfClasses': 0.0, 'NumberOfFeatures': 14.0, 'NumberOfInstances': 270.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 14.0, 'NumberOfSymbolicFeatures': 0.0, 'cos...
heart
[ "att_1", "att_2", "att_3", "att_4", "att_5", "att_6", "att_7", "att_8", "att_9", "att_10", "att_11", "att_12", "att_13" ]
[ false, false, false, false, false, false, false, false, false, false, false, false, false ]
603
211,841
mean_absolute_error
mean_absolute_error
fourclass_scale
**Author**: Tin Kam Ho and Eugene M. Kleinberg. libSVM","AAD group **Source**: [original](http://www.csie.ntu.edu.tw/~cjlin/libsvmtools/datasets/binary.html) - Date unknown **Please cite**: #Dataset from the LIBSVM data repository. Preprocessing: transform to two-class
{0: [0 - att_1 (numeric)], 1: [1 - att_2 (numeric)], 2: [2 - class (numeric)]}
{'MajorityClassSize': nan, 'MaxNominalAttDistinctValues': nan, 'MinorityClassSize': nan, 'NumberOfClasses': 0.0, 'NumberOfFeatures': 3.0, 'NumberOfInstances': 862.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 3.0, 'NumberOfSymbolicFeatures': 0.0, 'cost_...
fourclass_scale
[ "att_1", "att_2" ]
[ false, false ]
604
5,235
mean_absolute_error
mean_absolute_error
fri_c3_250_5
**Author**: **Source**: Unknown - Date unknown **Please cite**: The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as "fri_colinearintydegree_samplenumber_featurenumber". Friedman is the one of the most...
{0: [0 - oz1 (numeric)], 1: [1 - oz2 (numeric)], 2: [2 - oz3 (numeric)], 3: [3 - oz4 (numeric)], 4: [4 - oz5 (numeric)], 5: [5 - oz6 (numeric)]}
{'MajorityClassSize': nan, 'MaxNominalAttDistinctValues': nan, 'MinorityClassSize': nan, 'NumberOfClasses': 0.0, 'NumberOfFeatures': 6.0, 'NumberOfInstances': 250.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 6.0, 'NumberOfSymbolicFeatures': 0.0, 'cost_...
fri_c3_250_5
[ "oz1", "oz2", "oz3", "oz4", "oz5" ]
[ false, false, false, false, false ]
605
5,239
mean_absolute_error
mean_absolute_error
fri_c3_500_5
**Author**: **Source**: Unknown - Date unknown **Please cite**: The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as "fri_colinearintydegree_samplenumber_featurenumber". Friedman is the one of the most...
{0: [0 - oz1 (numeric)], 1: [1 - oz2 (numeric)], 2: [2 - oz3 (numeric)], 3: [3 - oz4 (numeric)], 4: [4 - oz5 (numeric)], 5: [5 - oz6 (numeric)]}
{'MajorityClassSize': nan, 'MaxNominalAttDistinctValues': nan, 'MinorityClassSize': nan, 'NumberOfClasses': 0.0, 'NumberOfFeatures': 6.0, 'NumberOfInstances': 500.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 6.0, 'NumberOfSymbolicFeatures': 0.0, 'cost_...
fri_c3_500_5
[ "oz1", "oz2", "oz3", "oz4", "oz5" ]
[ false, false, false, false, false ]
606
5,040
mean_absolute_error
mean_absolute_error
EgyptianSkulls
**Author**: **Source**: Unknown - Date unknown **Please cite**: Datasets of Data And Story Library, project illustrating use of basic statistic methods, converted to arff format by Hakan Kjellerstrand. Source: TunedIT: http://tunedit.org/repo/DASL DASL file http://lib.stat.cmu.edu/DASL/Datafiles/EgyptianSkull...
{0: [0 - MB (numeric)], 1: [1 - BH (numeric)], 2: [2 - BL (numeric)], 3: [3 - NH (numeric)], 4: [4 - Year (numeric)]}
{'MajorityClassSize': nan, 'MaxNominalAttDistinctValues': nan, 'MinorityClassSize': nan, 'NumberOfClasses': 0.0, 'NumberOfFeatures': 5.0, 'NumberOfInstances': 150.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 5.0, 'NumberOfSymbolicFeatures': 0.0, 'cost_...
EgyptianSkulls
[ "MB", "BH", "BL", "NH" ]
[ false, false, false, false ]
607
5,243
mean_absolute_error
mean_absolute_error
fri_c0_100_10
**Author**: **Source**: Unknown - Date unknown **Please cite**: The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as "fri_colinearintydegree_samplenumber_featurenumber". Friedman is the one of the most...
{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)]}
{'MajorityClassSize': nan, 'MaxNominalAttDistinctValues': nan, 'MinorityClassSize': nan, 'NumberOfClasses': 0.0, 'NumberOfFeatures': 11.0, 'NumberOfInstances': 100.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 11.0, 'NumberOfSymbolicFeatures': 0.0, 'cos...
fri_c0_100_10
[ "oz1", "oz2", "oz3", "oz4", "oz5", "oz6", "oz7", "oz8", "oz9", "oz10" ]
[ false, false, false, false, false, false, false, false, false, false ]
608
5,241
mean_absolute_error
mean_absolute_error
fri_c4_250_50
**Author**: **Source**: Unknown - Date unknown **Please cite**: The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as "fri_colinearintydegree_samplenumber_featurenumber". Friedman is the one of the most...
{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': 51.0, 'NumberOfInstances': 250.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 51.0, 'NumberOfSymbolicFeatures': 0.0, 'cos...
fri_c4_250_50
[ "oz1", "oz2", "oz3", "oz4", "oz5", "oz6", "oz7", "oz8", "oz9", "oz10", "oz11", "oz12", "oz13", "oz14", "oz15", "oz16", "oz17", "oz18", "oz19", "oz20", "oz21", "oz22", "oz23", "oz24", "oz25", "oz26", "oz27", "oz28", "oz29", "oz30", "oz31", "oz32", "oz33...
[ false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, f...
609
211,792
predictive_accuracy
accuracy_score
splice
**Author**: Delve Datasets libSVM","AAD group **Source**: [original](http://www.csie.ntu.edu.tw/~cjlin/libsvmtools/datasets/binary.html) - Date unknown **Please cite**: #Dataset from the LIBSVM data repository. Preprocessing: scaled to [-1,1]
{0: [0 - att_1 (numeric)], 1: [1 - att_2 (numeric)], 2: [2 - att_3 (numeric)], 3: [3 - att_4 (numeric)], 4: [4 - att_5 (numeric)], 5: [5 - att_6 (numeric)], 6: [6 - att_7 (numeric)], 7: [7 - att_8 (numeric)], 8: [8 - att_9 (numeric)], 9: [9 - att_10 (numeric)], 10: [10 - att_11 (numeric)], 11: [11 - att_12 (...
{'MajorityClassSize': nan, 'MaxNominalAttDistinctValues': nan, 'MinorityClassSize': nan, 'NumberOfClasses': 0.0, 'NumberOfFeatures': 61.0, 'NumberOfInstances': 3175.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 61.0, 'NumberOfSymbolicFeatures': 0.0, 'co...
splice
[ "att_1", "att_2", "att_3", "att_4", "att_5", "att_6", "att_7", "att_8", "att_9", "att_10", "att_11", "att_12", "att_13", "att_14", "att_15", "att_16", "att_17", "att_18", "att_19", "att_20", "att_21", "att_22", "att_23", "att_24", "att_25", "att_26", "att_27", "...
[ false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, f...
610
211,842
mean_absolute_error
mean_absolute_error
german.numer
null
{0: [0 - att_1 (numeric)], 1: [1 - att_2 (numeric)], 2: [2 - att_3 (numeric)], 3: [3 - att_4 (numeric)], 4: [4 - att_5 (numeric)], 5: [5 - att_6 (numeric)], 6: [6 - att_7 (numeric)], 7: [7 - att_8 (numeric)], 8: [8 - att_9 (numeric)], 9: [9 - att_10 (numeric)], 10: [10 - att_11 (numeric)], 11: [11 - att_12 (...
{'MajorityClassSize': nan, 'MaxNominalAttDistinctValues': nan, 'MinorityClassSize': nan, 'NumberOfClasses': 0.0, 'NumberOfFeatures': 25.0, 'NumberOfInstances': 1000.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 25.0, 'NumberOfSymbolicFeatures': 0.0, 'co...
german.numer
[ "att_1", "att_2", "att_3", "att_4", "att_5", "att_6", "att_7", "att_8", "att_9", "att_10", "att_11", "att_12", "att_13", "att_14", "att_15", "att_16", "att_17", "att_18", "att_19", "att_20", "att_21", "att_22", "att_23", "att_24" ]
[ false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false ]
611
211,780
predictive_accuracy
accuracy_score
colon-cancer
**Author**: U. Alon","N. Barkai","D. A. Notterman","K. Gish","S.Ybarra","D.Mack","and A. J. Levine. libSVM","AAD group **Source**: [original](http://www.csie.ntu.edu.tw/~cjlin/libsvmtools/datasets/binary.html) - Date unknown **Please cite**: U. Alon, N. Barkai, D. A. Notterman, K. Gish, S.Ybarra, D.Mack, and A. J...
{0: [0 - att_1 (numeric)], 1: [1 - att_2 (numeric)], 2: [2 - att_3 (numeric)], 3: [3 - att_4 (numeric)], 4: [4 - att_5 (numeric)], 5: [5 - att_6 (numeric)], 6: [6 - att_7 (numeric)], 7: [7 - att_8 (numeric)], 8: [8 - att_9 (numeric)], 9: [9 - att_10 (numeric)], 10: [10 - att_11 (numeric)], 11: [11 - att_12 (...
{'MajorityClassSize': nan, 'MaxNominalAttDistinctValues': nan, 'MinorityClassSize': nan, 'NumberOfClasses': 0.0, 'NumberOfFeatures': 2001.0, 'NumberOfInstances': 62.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 2001.0, 'NumberOfSymbolicFeatures': 0.0, '...
colon-cancer
[ "att_1", "att_2", "att_3", "att_4", "att_5", "att_6", "att_7", "att_8", "att_9", "att_10", "att_11", "att_12", "att_13", "att_14", "att_15", "att_16", "att_17", "att_18", "att_19", "att_20", "att_21", "att_22", "att_23", "att_24", "att_25", "att_26", "att_27", "...
[ false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, f...
612
5,231
mean_absolute_error
mean_absolute_error
fri_c0_1000_5
**Author**: **Source**: Unknown - Date unknown **Please cite**: The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as "fri_colinearintydegree_samplenumber_featurenumber". Friedman is the one of the most...
{0: [0 - oz1 (numeric)], 1: [1 - oz2 (numeric)], 2: [2 - oz3 (numeric)], 3: [3 - oz4 (numeric)], 4: [4 - oz5 (numeric)], 5: [5 - oz6 (numeric)]}
{'MajorityClassSize': nan, 'MaxNominalAttDistinctValues': nan, 'MinorityClassSize': nan, 'NumberOfClasses': 0.0, 'NumberOfFeatures': 6.0, 'NumberOfInstances': 1000.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 6.0, 'NumberOfSymbolicFeatures': 0.0, 'cost...
fri_c0_1000_5
[ "oz1", "oz2", "oz3", "oz4", "oz5" ]
[ false, false, false, false, false ]
613
5,249
mean_absolute_error
mean_absolute_error
fri_c2_500_10
**Author**: **Source**: Unknown - Date unknown **Please cite**: The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as "fri_colinearintydegree_samplenumber_featurenumber". Friedman is the one of the most...
{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)]}
{'MajorityClassSize': nan, 'MaxNominalAttDistinctValues': nan, 'MinorityClassSize': nan, 'NumberOfClasses': 0.0, 'NumberOfFeatures': 11.0, 'NumberOfInstances': 500.0, 'NumberOfInstancesWithMissingValues': 0.0, 'NumberOfMissingValues': 0.0, 'NumberOfNumericFeatures': 11.0, 'NumberOfSymbolicFeatures': 0.0, 'cos...
fri_c2_500_10
[ "oz1", "oz2", "oz3", "oz4", "oz5", "oz6", "oz7", "oz8", "oz9", "oz10" ]
[ false, false, false, false, false, false, false, false, false, false ]
614