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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 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 likes1 downloads1 reach7 impact
323 instances - 5 features - 0 classes - 0 missing values
DATA-SETS FROM DIGGLE, P.J. (1990). TIME SERIES : A BIOSTATISTICAL INTRODUCTION. Oxford University Press. Table: Table A1 Lutenizing hormone Information about the dataset CLASSTYPE: numeric…
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48 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…
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46 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…
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70 instances - 5 features - 0 classes - 0 missing values
1. Title: Employee Selection (Ordinal ESL) 2. Source Informaion: Donor: Arie Ben David MIS, Dept. of Technology Management Holon Academic Inst. of Technology 52 Golomb St. Holon 58102 Israel…
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488 instances - 5 features - 0 classes - 0 missing values
1. Title: Employee Selection (Ordinal ESL) 2. Source Informaion: Donor: Arie Ben David MIS, Dept. of Technology Management Holon Academic Inst. of Technology 52 Golomb St. Holon 58102 Israel…
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488 instances - 5 features - 0 classes - 0 missing values
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 runs1 likes2 downloads3 reach5 impact
1000 instances - 5 features - 0 classes - 0 missing values
1. Title: Employee Rejection\Acceptance (Orinal ERA) 2. Source Informaion: Donor: Arie Ben David MIS, Dept. of Technology Management Holon Academic Inst. of Technology 52 Golomb St. Holon 58102 Israel…
0 runs0 likes1 downloads1 reach5 impact
1000 instances - 5 features - 0 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
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…
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39 instances - 5 features - 0 classes - 0 missing values
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…
0 runs0 likes1 downloads1 reach5 impact
150 instances - 5 features - 0 classes - 0 missing values
libSVM","AAD group A practical guide to support vector classification. Technical report, Department of Computer Science, National Taiwan University, 2003. #Dataset from the LIBSVM data repository…
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7089 instances - 5 features - 0 classes - 0 missing values
MyExampleIris
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150 instances - 5 features - 3 classes - 0 missing values
No data.
0 runs0 likes0 downloads0 reach3 impact
24 instances - 5 features - 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…
0 runs0 likes0 downloads0 reach5 impact
48 instances - 5 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
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
!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! Identifier attribute deleted. !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! NAME: Sexual activity and the lifespan of male fruitflies TYPE: Designed (almost factorial)…
4 runs0 likes2 downloads2 reach1 impact
125 instances - 5 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. Gasoline comnsumption is being treated as…
2 runs0 likes0 downloads0 reach1 impact
27 instances - 5 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. Points scored per minute is being treated as…
2 runs0 likes0 downloads0 reach1 impact
96 instances - 5 features - 0 classes - 0 missing values
Data originating from the book "Analyzing Categorical Data" by Jeffrey S. Simonoff.
1085 runs0 likes9 downloads9 reach7 impact
50 instances - 5 features - 2 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
The weather problem is a tiny dataset that we will use repeatedly to illustrate machine learning methods. Entirely fictitious, it supposedly concerns the conditions that are suitable for playing some…
0 runs0 likes0 downloads0 reach0 impact
14 instances - 5 features - 2 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
iris with ignored features Sepal.Width and Petal.Length
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150 instances - 5 features - 3 classes - 0 missing values
test openml upload
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150 instances - 5 features - 3 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
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
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 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
The weather problem is a tiny dataset that we will use repeatedly to illustrate machine learning methods. Entirely fictitious, it supposedly concerns the conditions that are suitable for playing some…
0 runs0 likes1 downloads1 reach1 impact
14 instances - 5 features - 2 classes - 0 missing values
The weather problem is a tiny dataset that we will use repeatedly to illustrate machine learning methods. Entirely fictitious, it supposedly concerns the conditions that are suitable for playing some…
0 runs0 likes0 downloads0 reach1 impact
14 instances - 5 features - 2 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
The weather problem is a tiny dataset that we will use repeatedly to illustrate machine learning methods. Entirely fictitious, it supposedly concerns the conditions that are suitable for playing some…
0 runs0 likes0 downloads0 reach0 impact
14 instances - 5 features - 2 classes - 0 missing values
The weather problem is a tiny dataset that we will use repeatedly to illustrate machine learning methods. Entirely fictitious, it supposedly concerns the conditions that are suitable for playing some…
0 runs0 likes1 downloads1 reach0 impact
14 instances - 5 features - 2 classes - 0 missing values
The weather problem is a tiny dataset that we will use repeatedly to illustrate machine learning methods. Entirely fictitious, it supposedly concerns the conditions that are suitable for playing some…
0 runs0 likes0 downloads0 reach0 impact
14 instances - 5 features - 2 classes - 0 missing values
The weather problem is a tiny dataset that we will use repeatedly to illustrate machine learning methods. Entirely fictitious, it supposedly concerns the conditions that are suitable for playing some…
0 runs0 likes0 downloads0 reach0 impact
14 instances - 5 features - 2 classes - 0 missing values
The weather problem is a tiny dataset that we will use repeatedly to illustrate machine learning methods. Entirely fictitious, it supposedly concerns the conditions that are suitable for playing some…
0 runs0 likes0 downloads0 reach0 impact
14 instances - 5 features - 2 classes - 0 missing values
The weather problem is a tiny dataset that we will use repeatedly to illustrate machine learning methods. Entirely fictitious, it supposedly concerns the conditions that are suitable for playing some…
0 runs0 likes0 downloads0 reach0 impact
14 instances - 5 features - 2 classes - 0 missing values
The weather problem is a tiny dataset that we will use repeatedly to illustrate machine learning methods. Entirely fictitious, it supposedly concerns the conditions that are suitable for playing some…
0 runs0 likes0 downloads0 reach0 impact
14 instances - 5 features - 2 classes - 0 missing values
test
0 runs0 likes0 downloads0 reach1 impact
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
* 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
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…
1041 runs0 likes10 downloads10 reach6 impact
125 instances - 5 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). The multi-class target feature is converted to a two-class nominal target feature by re-labeling the majority class as positive ('P') and…
777 runs0 likes8 downloads8 reach7 impact
625 instances - 5 features - 2 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…
886 runs0 likes8 downloads8 reach7 impact
264 instances - 5 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…
750 runs0 likes5 downloads5 reach6 impact
48 instances - 5 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 likes8 downloads8 reach7 impact
559 instances - 5 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…
117 runs0 likes7 downloads7 reach6 impact
50 instances - 5 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…
774 runs0 likes9 downloads9 reach7 impact
559 instances - 5 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…
812 runs0 likes7 downloads7 reach7 impact
559 instances - 5 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…
769 runs0 likes7 downloads7 reach7 impact
559 instances - 5 features - 2 classes - 0 missing values
This data set was generated to model psychological experimental results. Each example is classified as having the balance scale tip to the right, tip to the left, or be balanced. The attributes are…
26795 runs2 likes15 downloads17 reach3 impact
625 instances - 5 features - 3 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…
705 runs0 likes6 downloads6 reach6 impact
96 instances - 5 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…
707 runs0 likes9 downloads9 reach6 impact
48 instances - 5 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…
114 runs0 likes5 downloads5 reach6 impact
70 instances - 5 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…
773 runs0 likes11 downloads11 reach7 impact
8641 instances - 5 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…
121 runs0 likes6 downloads6 reach6 impact
46 instances - 5 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…
842 runs0 likes9 downloads9 reach7 impact
323 instances - 5 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). The multi-class target feature is converted to a two-class nominal target feature by re-labeling the majority class as positive ('P') and…
774 runs0 likes9 downloads9 reach7 impact
797 instances - 5 features - 2 classes - 0 missing values
One of the datasets used in the book "Analyzing Categorical Data," by Jeffrey S. Simonoff. It contains data on the DMFT Index (Decayed, Missing, and Filled Teeth) before and after different prevention…
26667 runs0 likes11 downloads11 reach34 impact
797 instances - 5 features - 6 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…
1058 runs0 likes9 downloads9 reach7 impact
167 instances - 5 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…
453 runs0 likes5 downloads5 reach6 impact
108 instances - 5 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). The multi-class target feature is converted to a two-class nominal target feature by re-labeling the majority class as positive ('P') and…
1133 runs0 likes15 downloads15 reach10 impact
150 instances - 5 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). The multi-class target feature is converted to a two-class nominal target feature by re-labeling the majority class as positive ('P') and…
1137 runs0 likes7 downloads7 reach6 impact
132 instances - 5 features - 2 classes - 0 missing values
Hayes-Roth Database This is a merged version of the separate train and test set which are usually distributed. On OpenML this train-test split can be found as one of the possible tasks. Source…
380 runs0 likes3 downloads3 reach16 impact
160 instances - 5 features - 3 classes - 0 missing values
classification
0 runs0 likes1 downloads1 reach0 impact
150 instances - 5 features - classes - 0 missing values