OpenML
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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
test openml upload
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150 instances - 5 features - 3 classes - 0 missing values
iris-example
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150 instances - 5 features - 3 classes - 0 missing values
test
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sqs efrf
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4 instances - 5 features - 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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50 instances - 5 features - 0 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
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
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 - 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 - 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 - 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 - classes - 0 missing values
test
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150 instances - 5 features - classes - 0 missing values
This is weather data in arff format
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14 instances - 5 features - 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…
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323 instances - 5 features - 0 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…
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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…
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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…
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14 instances - 5 features - 2 classes - 0 missing values
Iris DataSet
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150 instances - 5 features - 3 classes - 0 missing values
Information about the dataset CLASSTYPE: numeric CLASSINDEX: last
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559 instances - 5 features - 0 classes - 0 missing values
Information about the dataset CLASSTYPE: numeric CLASSINDEX: last
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559 instances - 5 features - 0 classes - 0 missing values
A shar archive of data from the book Data Analysis: An Introduction(1992) Prentice Hall bu Jeff Witmer. Submitted by Jeff Witmer (fwitmer@ocvaxa.cc.oberlin.edu) [28/Jun/94] (29 kbytes) Note:…
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50 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…
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96 instances - 5 features - 0 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 reach8 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…
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14 instances - 5 features - 2 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
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 reach8 impact
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 reach8 impact
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 reach8 impact
150 instances - 5 features - 3 classes - 0 missing values
iris with ignored features Sepal.Width and Petal.Length
0 runs0 likes0 downloads0 reach8 impact
150 instances - 5 features - classes - 0 missing values
iris with ignored features Sepal.Width and Petal.Length
0 runs0 likes0 downloads0 reach8 impact
150 instances - 5 features - 3 classes - 0 missing values
iris with ignored features Sepal.Width and Petal.Length
0 runs0 likes0 downloads0 reach8 impact
150 instances - 5 features - classes - 0 missing values
iris with ignored features Sepal.Width and Petal.Length
0 runs0 likes0 downloads0 reach8 impact
150 instances - 5 features - 3 classes - 0 missing values
iris with ignored features Sepal.Width and Petal.Length
0 runs0 likes0 downloads0 reach8 impact
150 instances - 5 features - classes - 0 missing values
iris with ignored features Sepal.Width and Petal.Length
0 runs0 likes0 downloads0 reach8 impact
150 instances - 5 features - 3 classes - 0 missing values
iris with ignored features Sepal.Width and Petal.Length
0 runs0 likes0 downloads0 reach8 impact
150 instances - 5 features - classes - 0 missing values
!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! Identifier attribute deleted. !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! NAME: Sexual activity and the lifespan of male fruitflies TYPE: Designed (almost factorial)…
4 runs0 likes2 downloads2 reach12 impact
125 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…
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48 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
tmm hjghjg vjgkjhbb nvhjgb
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748 instances - 5 features - classes - 0 missing values
Electrical-Maintenance data set This problem consists of four input variables and the available data set is comprised of a representative number of well distributed examples. In this case, the…
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1056 instances - 5 features - 0 classes - 0 missing values
This data set was originally a univariate time record of a single observed quantity, recorded from a Far-Infrared-Laser in a chaotic state. The original set 1000 points has been adapted for regression…
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993 instances - 5 features - 0 classes - 0 missing values
Data has been taken from various sources such as data gov and various other websites and has been pre processed for analysis purpose
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204 instances - 5 features - classes - 0 missing values
Data originating from the book "Analyzing Categorical Data" by Jeffrey S. Simonoff.
1087 runs0 likes9 downloads9 reach15 impact
50 instances - 5 features - 2 classes - 0 missing values
This dataset is synthetic. It was generated by David Coleman at RCA Laboratories in Princeton, N.J. For convenience, we will refer to it as the POLLEN DATA. The first three variables are the lengths…
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3848 instances - 5 features - 0 classes - 0 missing values
Information about the dataset CLASSTYPE: numeric CLASSINDEX: last
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559 instances - 5 features - 0 classes - 0 missing values
e3r4vr t4r
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2 instances - 5 features - classes - 0 missing values
f fr
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2 instances - 5 features - classes - 0 missing values
sample
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14 instances - 5 features - classes - 0 missing values
test data
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2 instances - 5 features - classes - 0 missing values
this is test data
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5 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
0 runs0 likes0 downloads0 reach2 impact
150 instances - 5 features - 3 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…
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27 instances - 5 features - 0 classes - 0 missing values
Information about the dataset CLASSTYPE: numeric CLASSINDEX: last
2 runs0 likes1 downloads1 reach13 impact
559 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 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 reach13 impact
8641 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 likes2 downloads2 reach11 impact
366 instances - 5 features - classes - 2 missing values
Author: Volker Lohweg (University of Applied Sciences, Ostwestfalen-Lippe) Source: [UCI](https://archive.ics.uci.edu/ml/datasets/banknote+authentication) - 2012 Please cite:…
137675 runs5 likes32 downloads37 reach30 impact
1372 instances - 5 features - 2 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 reach13 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 likes8 downloads8 reach15 impact
149332 instances - 5 features - 22 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 reach13 impact
1000 instances - 5 features - 0 classes - 0 missing values
MyExampleIris
32 runs0 likes1 downloads1 reach20 impact
150 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…
1043 runs0 likes10 downloads10 reach14 impact
125 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…
1058 runs0 likes9 downloads9 reach15 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…
707 runs0 likes6 downloads6 reach14 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…
709 runs0 likes9 downloads9 reach14 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…
117 runs0 likes4 downloads4 reach14 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…
752 runs0 likes5 downloads5 reach14 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…
812 runs0 likes7 downloads7 reach15 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…
774 runs0 likes9 downloads9 reach15 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 reach15 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…
779 runs0 likes8 downloads8 reach15 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…
773 runs0 likes12 downloads12 reach15 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…
842 runs0 likes9 downloads9 reach15 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…
777 runs0 likes8 downloads8 reach15 impact
625 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…
113 runs0 likes3 downloads3 reach15 impact
366 instances - 5 features - 2 classes - 1 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…
1139 runs0 likes7 downloads7 reach14 impact
132 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…
1136 runs0 likes15 downloads15 reach18 impact
150 instances - 5 features - 2 classes - 0 missing values
No data.
0 runs0 likes0 downloads0 reach11 impact
24 instances - 5 features - 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…
467766 runs5 likes86 downloads91 reach41 impact
748 instances - 5 features - 2 classes - 0 missing values