OpenML
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Normalized version of the pokerhand data set. Automated file upload of pokerhand-normalized.arff
314 runs0 likes11 downloads11 reach2 impact
829201 instances - 11 features - 10 classes - 0 missing values
cleve-pmlb
32 runs0 likes1 downloads1 reach11 impact
303 instances - 14 features - 2 classes - 0 missing values
new-thyroid-pmlb
31 runs0 likes2 downloads2 reach11 impact
215 instances - 6 features - 3 classes - 0 missing values
__Changes w.r.t. version 1: renamed variables such that they match description.__ ### Dataset: Wilt Data Set ### Abstract: High-resolution Remote Sensing data set (Quickbird). Small number of training…
8029 runs0 likes1 downloads1 reach11 impact
4839 instances - 6 features - 2 classes - 0 missing values
Estimated article influence scores in 2015
0 runs0 likes0 downloads0 reach0 impact
3615 instances - 7 features - 3169 classes - 48 missing values
General Description 2015-current: greater than $200.00. The Commission categorizes contributions from individuals using the calendar year-to-date amount for political action committee (PAC) and party…
0 runs0 likes0 downloads0 reach0 impact
3348209 instances - 21 features - 0 classes - 10786577 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
1173 runs0 likes8 downloads8 reach6 impact
100 instances - 6 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
847 runs0 likes7 downloads7 reach7 impact
250 instances - 6 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
624 runs0 likes8 downloads8 reach7 impact
1000 instances - 6 features - 2 classes - 0 missing values
PRO FOOTBALL SCORES (raw data appears after the description below) How well do the oddsmakers of Las Vegas predict the outcome of professional football games? Is there really a home field advantage -…
15927 runs0 likes19 downloads19 reach17 impact
672 instances - 10 features - 2 classes - 1200 missing values
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…
117 runs0 likes5 downloads5 reach6 impact
50 instances - 7 features - 2 classes - 0 missing values
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% This is a PROMISE Software Engineering Repository data set made publicly available in order to encourage repeatable,…
109963 runs1 likes19 downloads20 reach19 impact
15545 instances - 6 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
777 runs0 likes8 downloads8 reach7 impact
500 instances - 6 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
1136 runs0 likes8 downloads8 reach6 impact
100 instances - 6 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
706 runs0 likes5 downloads5 reach6 impact
62 instances - 6 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
1111 runs0 likes9 downloads9 reach6 impact
100 instances - 6 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
854 runs0 likes7 downloads7 reach7 impact
250 instances - 6 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
672 runs0 likes4 downloads4 reach7 impact
158 instances - 8 features - 2 classes - 87 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
721 runs0 likes5 downloads5 reach6 impact
34 instances - 9 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
594 runs0 likes8 downloads8 reach7 impact
1000 instances - 6 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
822 runs0 likes7 downloads7 reach7 impact
250 instances - 6 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
853 runs0 likes7 downloads7 reach7 impact
250 instances - 6 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
787 runs0 likes7 downloads7 reach6 impact
73 instances - 6 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
778 runs0 likes7 downloads7 reach6 impact
66 instances - 6 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
786 runs0 likes7 downloads7 reach7 impact
500 instances - 6 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
631 runs0 likes7 downloads7 reach7 impact
1000 instances - 6 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
806 runs0 likes8 downloads8 reach7 impact
500 instances - 6 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
802 runs0 likes14 downloads14 reach7 impact
3848 instances - 6 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
757 runs0 likes6 downloads6 reach6 impact
50 instances - 6 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
779 runs0 likes7 downloads7 reach7 impact
500 instances - 6 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
598 runs0 likes8 downloads8 reach7 impact
1000 instances - 6 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
866 runs1 likes11 downloads12 reach8 impact
7129 instances - 6 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
1119 runs0 likes8 downloads8 reach6 impact
100 instances - 6 features - 2 classes - 0 missing values
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 infection,…
2 runs0 likes0 downloads0 reach5 impact
76 instances - 7 features - 0 classes - 0 missing values
This S dump contains 22 data sets from the book Visualizing Data published by Hobart Press (books@hobart.com). The dump was created by data.dump() and can be read back into S by data.restore(). The…
0 runs0 likes2 downloads2 reach5 impact
44 instances - 4 features - 0 classes - 0 missing values
Data Used in "A BAYESIAN APPROACH TO DATA DISCLOSURE: OPTIMAL INTRUDER BEHAVIOR FOR CONTINUOUS DATA" by Stephen E. Fienberg, Udi E. Makov, and Ashish P. Sanil Background: ========== In this paper we…
0 runs0 likes0 downloads0 reach5 impact
662 instances - 4 features - 0 classes - 0 missing values
This S dump contains 22 data sets from the book Visualizing Data published by Hobart Press (books@hobart.com). The dump was created by data.dump() and can be read back into S by data.restore(). The…
0 runs0 likes0 downloads0 reach5 impact
111 instances - 4 features - 0 classes - 0 missing values
Data taken from the Blood Transfusion Service Center in Hsin-Chu City in Taiwan -- this is a classification problem. To demonstrate the RFMTC marketing model (a modified version of RFM), this study…
464417 runs3 likes60 downloads63 reach28 impact
748 instances - 5 features - 2 classes - 0 missing values
File README ----------- chscase A collection of the data sets used in the book "A Casebook for a First Course in Statistics and Data Analysis," by Samprit Chatterjee, Mark S. Handcock and Jeffrey S.…
14 runs0 likes0 downloads0 reach5 impact
526 instances - 6 features - 0 classes - 0 missing values
Data Used in "A BAYESIAN APPROACH TO DATA DISCLOSURE: OPTIMAL INTRUDER BEHAVIOR FOR CONTINUOUS DATA" by Stephen E. Fienberg, Udi E. Makov, and Ashish P. Sanil Background: ========== In this paper we…
0 runs0 likes0 downloads0 reach5 impact
662 instances - 4 features - 0 classes - 0 missing values
Data Used in "A BAYESIAN APPROACH TO DATA DISCLOSURE: OPTIMAL INTRUDER BEHAVIOR FOR CONTINUOUS DATA" by Stephen E. Fienberg, Udi E. Makov, and Ashish P. Sanil Background: ========== In this paper we…
0 runs0 likes1 downloads1 reach5 impact
662 instances - 4 features - 0 classes - 0 missing values
Graeme D. Hutcheson and Nick Sofroniou 1999 The Multivariate Social Scientist: Introductory Statistics Using Generalized Linear Models. SAGE Publications. Copyright: Graeme D. Hutcheson & Nick…
2 runs0 likes0 downloads0 reach5 impact
70 instances - 8 features - 0 classes - 0 missing values
This S dump contains 22 data sets from the book Visualizing Data published by Hobart Press (books@hobart.com). The dump was created by data.dump() and can be read back into S by data.restore(). The…
2 runs0 likes1 downloads1 reach5 impact
8641 instances - 5 features - 0 classes - 0 missing values
This file contains data from Regression Analysis By Example, 2nd Edition, by Samprit Chatterjee and Bertram Price, John Wiley, 1991. Data sets have names of the form 'rabe.xxx' where xxx is the page…
0 runs0 likes0 downloads0 reach5 impact
46 instances - 5 features - 0 classes - 0 missing values
Data Used in "A BAYESIAN APPROACH TO DATA DISCLOSURE: OPTIMAL INTRUDER BEHAVIOR FOR CONTINUOUS DATA" by Stephen E. Fienberg, Udi E. Makov, and Ashish P. Sanil Background: ========== In this paper we…
0 runs0 likes0 downloads0 reach5 impact
662 instances - 4 features - 0 classes - 0 missing values
* Dataset Title: Wall-Following Robot Navigation Data Data Set (version with 4 Attributes) * Abstract: The data were collected as the SCITOS G5 robot navigates through the room following the wall in a…
138 runs1 likes6 downloads7 reach7 impact
5456 instances - 5 features - 4 classes - 0 missing values
The dataset collects data from an Android smartphone positioned in the chest pocket. Accelerometer Data are collected from 22 participants walking in the wild over a predefined path. The dataset is…
80 runs0 likes7 downloads7 reach6 impact
149332 instances - 5 features - 22 classes - 0 missing values
%-*- text -*- %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% This is a PROMISE Software Engineering Repository data set made publicly available in order to encourage…
2 runs0 likes2 downloads2 reach5 impact
93 instances - 24 features - 0 classes - 0 missing values
DATA FILE: Data on patient deaths within 30 days of surgery in 131 U.S. hospitals. See Christiansen and Morris, Bayesian Biostatistics, D. Berry and D. Stangl, editors, 1996, Marcel Dekker, Inc. Data…
0 runs0 likes0 downloads0 reach5 impact
131 instances - 4 features - 0 classes - 0 missing values
File README ----------- smoothmeth A collection of the data sets used in the book "Smoothing Methods in Statistics," by Jeffrey S. Simonoff, Springer-Verlag, New York, 1996. Submitted by Jeff Simonoff…
0 runs0 likes0 downloads0 reach5 impact
2178 instances - 4 features - 0 classes - 0 missing values
MyExampleIris
32 runs0 likes0 downloads0 reach11 impact
150 instances - 5 features - 3 classes - 0 missing values
Information about the dataset CLASSTYPE: numeric CLASSINDEX: last
2 runs0 likes1 downloads1 reach5 impact
559 instances - 5 features - 0 classes - 0 missing values
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…
2 runs0 likes0 downloads0 reach5 impact
120 instances - 20 features - 0 classes - 0 missing values
Information about the dataset CLASSTYPE: numeric CLASSINDEX: last
2 runs0 likes0 downloads0 reach5 impact
559 instances - 5 features - 0 classes - 0 missing values
Determinants of Wages from the 1985 Current Population Survey Summary: The Current Population Survey (CPS) is used to supplement census information between census years. These data consist of a random…
2 runs0 likes3 downloads3 reach5 impact
534 instances - 11 features - 0 classes - 0 missing values
Information about the dataset CLASSTYPE: numeric CLASSINDEX: last
2 runs0 likes1 downloads1 reach5 impact
559 instances - 5 features - 0 classes - 0 missing values
Information about the dataset CLASSTYPE: numeric CLASSINDEX: last
2 runs0 likes1 downloads1 reach5 impact
559 instances - 5 features - 0 classes - 0 missing values
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…
2 runs0 likes0 downloads0 reach5 impact
163 instances - 6 features - 0 classes - 0 missing values
Veteran's Administration Lung Cancer Trial Taken from Kalbfleisch and Prentice, pages 223-224 Variables Treatment 1=standard, 2=test Celltype 1=squamous, 2=smallcell, 3=adeno, 4=large Survival in days…
2 runs0 likes1 downloads1 reach5 impact
137 instances - 8 features - 0 classes - 0 missing values
Dataset from Smoothing Methods in Statistics (ftp stat.cmu.edu/datasets) Simonoff, J.S. (1996). Smoothing Methods in Statistics. New York: Springer-Verlag.
2 runs0 likes0 downloads0 reach1 impact
52 instances - 4 features - 0 classes - 0 missing values
Dataset from Smoothing Methods in Statistics (ftp stat.cmu.edu/datasets) Simonoff, J.S. (1996). Smoothing Methods in Statistics. New York: Springer-Verlag.
2 runs0 likes1 downloads1 reach1 impact
2178 instances - 4 features - 0 classes - 0 missing values
iris with ignored features Sepal.Width and Petal.Length
0 runs0 likes1 downloads1 reach1 impact
150 instances - 5 features - 3 classes - 0 missing values
iris with ignored features Sepal.Width and Petal.Length
0 runs0 likes0 downloads0 reach1 impact
150 instances - 5 features - classes - 0 missing values
iris with ignored features Sepal.Width and Petal.Length
0 runs0 likes0 downloads0 reach1 impact
150 instances - 5 features - classes - 0 missing values
iris with ignored features Sepal.Width and Petal.Length
0 runs0 likes0 downloads0 reach1 impact
150 instances - 5 features - 3 classes - 0 missing values
iris with ignored features Sepal.Width and Petal.Length
0 runs0 likes0 downloads0 reach1 impact
150 instances - 5 features - classes - 0 missing values
iris with ignored features Sepal.Width and Petal.Length
0 runs0 likes0 downloads0 reach1 impact
150 instances - 5 features - 3 classes - 0 missing values
test
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150 instances - 5 features - classes - 0 missing values
test
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150 instances - 5 features - classes - 0 missing values
test
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150 instances - 5 features - classes - 0 missing values
test
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150 instances - 5 features - classes - 0 missing values
iris with ignored features Sepal.Width and Petal.Length
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150 instances - 5 features - classes - 0 missing values
iris with ignored features Sepal.Width and Petal.Length
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150 instances - 5 features - 3 classes - 0 missing values
classification
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150 instances - 5 features - classes - 0 missing values
iris with ignored features Sepal.Width and Petal.Length
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150 instances - 5 features - classes - 0 missing values
iris with ignored features Sepal.Width and Petal.Length
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150 instances - 5 features - 3 classes - 0 missing values
Annual salary information including gross pay and overtime pay for all active, permanent employees of Montgomery County, MD paid in calendar year 2016. This information will be published annually each…
0 runs0 likes0 downloads0 reach0 impact
9228 instances - 13 features - 0 classes - 11169 missing values
iris with ignored features Sepal.Width and Petal.Length
0 runs0 likes0 downloads0 reach0 impact
150 instances - 5 features - 3 classes - 0 missing values
test openml upload
0 runs0 likes0 downloads0 reach1 impact
150 instances - 5 features - 3 classes - 0 missing values
iris with ignored features Sepal.Width and Petal.Length
0 runs0 likes0 downloads0 reach0 impact
150 instances - 5 features - classes - 0 missing values
iris with ignored features Sepal.Width and Petal.Length
0 runs0 likes0 downloads0 reach0 impact
150 instances - 5 features - 3 classes - 0 missing values
iris with ignored features Sepal.Width and Petal.Length
0 runs0 likes0 downloads0 reach0 impact
150 instances - 5 features - classes - 0 missing values
iris with ignored features Sepal.Width and Petal.Length
0 runs0 likes0 downloads0 reach0 impact
150 instances - 5 features - 3 classes - 0 missing values
iris with ignored features Sepal.Width and Petal.Length
0 runs0 likes0 downloads0 reach0 impact
150 instances - 5 features - classes - 0 missing values
iris with ignored features Sepal.Width and Petal.Length
0 runs0 likes0 downloads0 reach0 impact
150 instances - 5 features - 3 classes - 0 missing values
iris with ignored features Sepal.Width and Petal.Length
0 runs0 likes0 downloads0 reach0 impact
150 instances - 5 features - classes - 0 missing values
iris with ignored features Sepal.Width and Petal.Length
0 runs0 likes0 downloads0 reach0 impact
150 instances - 5 features - 3 classes - 0 missing values
iris with ignored features Sepal.Width and Petal.Length
0 runs0 likes0 downloads0 reach0 impact
150 instances - 5 features - classes - 0 missing values
iris with ignored features Sepal.Width and Petal.Length
0 runs0 likes0 downloads0 reach0 impact
150 instances - 5 features - 3 classes - 0 missing values
iris with ignored features Sepal.Width and Petal.Length
0 runs0 likes0 downloads0 reach0 impact
150 instances - 5 features - classes - 0 missing values
iris with ignored features Sepal.Width and Petal.Length
0 runs0 likes0 downloads0 reach0 impact
150 instances - 5 features - 3 classes - 0 missing values
iris with ignored features Sepal.Width and Petal.Length
0 runs0 likes0 downloads0 reach0 impact
150 instances - 5 features - classes - 0 missing values
iris with ignored features Sepal.Width and Petal.Length
0 runs0 likes0 downloads0 reach0 impact
150 instances - 5 features - 3 classes - 0 missing values
iris with ignored features Sepal.Width and Petal.Length
0 runs0 likes0 downloads0 reach0 impact
150 instances - 5 features - classes - 0 missing values
iris with ignored features Sepal.Width and Petal.Length
0 runs0 likes0 downloads0 reach0 impact
150 instances - 5 features - 3 classes - 0 missing values
iris with ignored features Sepal.Width and Petal.Length
0 runs0 likes0 downloads0 reach0 impact
150 instances - 5 features - classes - 0 missing values
iris with ignored features Sepal.Width and Petal.Length
0 runs0 likes0 downloads0 reach0 impact
150 instances - 5 features - 3 classes - 0 missing values
iris with ignored features Sepal.Width and Petal.Length
0 runs0 likes0 downloads0 reach0 impact
150 instances - 5 features - classes - 0 missing values
iris with ignored features Sepal.Width and Petal.Length
0 runs0 likes0 downloads0 reach0 impact
150 instances - 5 features - 3 classes - 0 missing values
iris with ignored features Sepal.Width and Petal.Length
0 runs0 likes0 downloads0 reach0 impact
150 instances - 5 features - classes - 0 missing values