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296 runs0 likes7 downloads7 reach1 impact
1000000 instances - 61 features - 2 classes - 0 missing values
Test dataset
2 runs0 likes0 downloads0 reach6 impact
15547 instances - 61 features - 2 classes - 280 missing values
The goal of this challenge is to expose the research community to real world datasets of interest to 4Paradigm. All datasets are formatted in a uniform way, though the type of data might differ. The…
0 runs0 likes0 downloads0 reach6 impact
416188 instances - 61 features - 355 classes - 0 missing values
### Description Synthetic Control Chart Time Series. This is actually time series classification. ### Sources ``` * Original Owner and Donor Dr Robert Alcock rob@skyblue.csd.auth.gr ``` ### Dataset…
20354 runs0 likes10 downloads10 reach40 impact
600 instances - 62 features - 6 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…
169 runs0 likes8 downloads8 reach8 impact
600 instances - 62 features - 2 classes - 0 missing values
NAME: Sonar, Mines vs. Rocks SUMMARY: This is the data set used by Gorman and Sejnowski in their study of the classification of sonar signals using a neural network [1]. The task is to train a network…
2366 runs1 likes24 downloads25 reach1 impact
208 instances - 61 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
186 instances - 61 features - 2 classes - 0 missing values
This data was gathered from participants in experimental speed dating events from 2002-2004. During the events, the attendees would have a four-minute "first date" with every other participant of the…
28058 runs16 likes150 downloads166 reach24 impact
8378 instances - 123 features - 2 classes - 18372 missing values
* Dataset Title: AutoUniv Dataset data problem: autoUniv-au4-2500 * Abstract: AutoUniv is an advanced data generator for classifications tasks. The aim is to reflect the nuances and heterogeneity of…
4222 runs0 likes7 downloads7 reach19 impact
2500 instances - 101 features - 3 classes - 0 missing values
SPAM E-mail Database The "spam" concept is diverse: advertisements for products/websites, make money fast schemes, chain letters, pornography... Our collection of spam e-mails came from our postmaster…
158564 runs3 likes82 downloads85 reach2 impact
4601 instances - 58 features - 2 classes - 0 missing values
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…
0 runs0 likes0 downloads0 reach5 impact
31 instances - 54 features - 0 classes - 0 missing values
This is the famous covertype dataset in its binary version, retrieved 2013-11-13 from the libSVM site (called covtype.binary there). Additional to the preprocessing done there (see LibSVM site for…
22 runs0 likes8 downloads8 reach7 impact
581012 instances - 55 features - 2 classes - 0 missing values
The goal of this challenge is to expose the research community to real world datasets of interest to 4Paradigm. All datasets are formatted in a uniform way, though the type of data might differ. The…
6 runs0 likes1 downloads1 reach7 impact
83733 instances - 55 features - 4 classes - 0 missing values
The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as…
0 runs0 likes1 downloads1 reach5 impact
1000 instances - 51 features - 0 classes - 0 missing values
The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as…
0 runs0 likes0 downloads0 reach5 impact
100 instances - 51 features - 0 classes - 0 missing values
The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as…
0 runs0 likes1 downloads1 reach5 impact
1000 instances - 51 features - 0 classes - 0 missing values
The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as…
0 runs0 likes0 downloads0 reach5 impact
100 instances - 51 features - 0 classes - 0 missing values
The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as…
0 runs0 likes0 downloads0 reach5 impact
500 instances - 51 features - 0 classes - 0 missing values
The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as…
0 runs0 likes0 downloads0 reach5 impact
250 instances - 51 features - 0 classes - 0 missing values
The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as…
0 runs0 likes0 downloads0 reach5 impact
500 instances - 51 features - 0 classes - 0 missing values
Source: James P Bridge, Sean B Holden and Lawrence C Paulson University of Cambridge Computer Laboratory William Gates Building 15 JJ Thomson Avenue Cambridge CB3 0FD UK +44 (0)1223 763500…
24391 runs1 likes20 downloads21 reach34 impact
6118 instances - 52 features - 6 classes - 0 missing values
The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as…
0 runs0 likes2 downloads2 reach5 impact
100 instances - 51 features - 0 classes - 0 missing values
The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as…
0 runs0 likes0 downloads0 reach5 impact
250 instances - 51 features - 0 classes - 0 missing values
The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as…
0 runs0 likes0 downloads0 reach5 impact
100 instances - 51 features - 0 classes - 0 missing values
The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as…
0 runs0 likes0 downloads0 reach5 impact
500 instances - 51 features - 0 classes - 0 missing values
The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as…
0 runs0 likes0 downloads0 reach5 impact
250 instances - 51 features - 0 classes - 0 missing values
The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as…
0 runs0 likes1 downloads1 reach5 impact
1000 instances - 51 features - 0 classes - 0 missing values
The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as…
0 runs0 likes0 downloads0 reach5 impact
500 instances - 51 features - 0 classes - 0 missing values
The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as…
0 runs0 likes0 downloads0 reach5 impact
100 instances - 51 features - 0 classes - 0 missing values
The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as…
0 runs0 likes0 downloads0 reach5 impact
500 instances - 51 features - 0 classes - 0 missing values
The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as…
0 runs0 likes1 downloads1 reach5 impact
1000 instances - 51 features - 0 classes - 0 missing values
The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as…
0 runs0 likes0 downloads0 reach5 impact
250 instances - 51 features - 0 classes - 0 missing values
The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as…
0 runs0 likes0 downloads0 reach5 impact
250 instances - 51 features - 0 classes - 0 missing values
The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as…
0 runs0 likes1 downloads1 reach5 impact
1000 instances - 51 features - 0 classes - 0 missing values
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…
0 runs0 likes0 downloads0 reach5 impact
14 instances - 51 features - 0 classes - 0 missing values
This dataset is taken from the MiniBooNE experiment and is used to distinguish electron neutrinos (signal) from muon neutrinos (background). This dataset is ordered. It first contains all signal…
6 runs0 likes2 downloads2 reach4 impact
130064 instances - 51 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…
621 runs0 likes8 downloads8 reach7 impact
1000 instances - 51 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…
620 runs0 likes10 downloads10 reach7 impact
1000 instances - 51 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…
784 runs0 likes7 downloads7 reach7 impact
500 instances - 51 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…
636 runs0 likes8 downloads8 reach7 impact
1000 instances - 51 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…
764 runs0 likes6 downloads6 reach6 impact
100 instances - 51 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…
801 runs0 likes8 downloads8 reach7 impact
500 instances - 51 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…
646 runs0 likes9 downloads9 reach7 impact
1000 instances - 51 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 likes6 downloads6 reach6 impact
100 instances - 51 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…
772 runs0 likes7 downloads7 reach7 impact
500 instances - 51 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…
817 runs0 likes7 downloads7 reach7 impact
250 instances - 51 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…
748 runs0 likes6 downloads6 reach7 impact
250 instances - 51 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…
766 runs0 likes7 downloads7 reach6 impact
100 instances - 51 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…
781 runs0 likes8 downloads8 reach7 impact
500 instances - 51 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…
755 runs0 likes6 downloads6 reach7 impact
250 instances - 51 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…
614 runs0 likes9 downloads9 reach7 impact
1000 instances - 51 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…
788 runs0 likes7 downloads7 reach6 impact
100 instances - 51 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 likes6 downloads6 reach7 impact
250 instances - 51 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…
775 runs0 likes6 downloads6 reach7 impact
250 instances - 51 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…
810 runs0 likes6 downloads6 reach6 impact
100 instances - 51 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…
807 runs0 likes7 downloads7 reach7 impact
500 instances - 51 features - 2 classes - 0 missing values
This is a commercial application described in Weiss & Indurkhya (1995). The data describes a telecommunication problem. No further information is available. Characteristics: (10000+5000) cases, 49…
2 runs0 likes3 downloads3 reach1 impact
15000 instances - 49 features - 0 classes - 0 missing values
Oil dataset Past Usage: 1. Kubat, M., Holte, R.,
200 runs3 likes17 downloads20 reach15 impact
937 instances - 50 features - 2 classes - 0 missing values
The goal of this challenge is to expose the research community to real world datasets of interest to 4Paradigm. All datasets are formatted in a uniform way, though the type of data might differ. The…
0 runs0 likes0 downloads0 reach6 impact
4147 instances - 49 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 likes10 downloads10 reach7 impact
15000 instances - 49 features - 2 classes - 0 missing values
These data are estimated correlations between daily 3 p.m. wind measurements during September and October 1997 for a network of 45 stations in the Sydney region. The first column below gives a list of…
0 runs0 likes0 downloads0 reach3 impact
45 instances - 47 features - classes - 0 missing values
No data.
52 runs0 likes3 downloads3 reach2 impact
1000000 instances - 48 features - 10 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…
792 runs0 likes8 downloads8 reach7 impact
2000 instances - 48 features - 2 classes - 0 missing values
One of a set of 6 datasets describing features of handwritten numerals (0 - 9) extracted from a collection of Dutch utility maps. Corresponding patterns in different datasets correspond to the same…
32604 runs0 likes21 downloads21 reach2 impact
2000 instances - 48 features - 10 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…
729 runs0 likes9 downloads9 reach6 impact
45 instances - 47 features - 2 classes - 0 missing values
This is a corrected version of the previous data file in version 1, which contained a dataset (349 instances) incorrectly merged from the original training and test sets available on UCI (there are…
0 runs0 likes2 downloads2 reach4 impact
267 instances - 45 features - 2 classes - 0 missing values
No data.
43 runs0 likes2 downloads2 reach1 impact
1000000 instances - 45 features - 2 classes - 0 missing values
No data.
47 runs0 likes1 downloads1 reach1 impact
1000000 instances - 45 features - 2 classes - 0 missing values
SPECTF heart data This is a merged version of the separate train and test set which are usually distributed. On OpenML this train-test split can be found as one of the possible tasks. NOTE: See the…
1103 runs0 likes12 downloads12 reach7 impact
349 instances - 45 features - 2 classes - 0 missing values
)), [PMLB](https://github.com/EpistasisLab/penn-ml-benchmarks/tree/master/datasets/classification/tokyo1) This is Performance co-pilot (PCP) data for the Tokyo server at Silicon Graphics International…
35 runs0 likes1 downloads1 reach12 impact
959 instances - 45 features - 2 classes - 0 missing values
QSAR biodegradation Data Set * Abstract: Data set containing values for 41 attributes (molecular descriptors) used to classify 1055 chemicals into 2 classes (ready and not ready biodegradable). *…
265103 runs1 likes17 downloads18 reach18 impact
1055 instances - 42 features - 2 classes - 0 missing values
No data.
0 runs0 likes0 downloads0 reach1 impact
1000000 instances - 41 features - 0 classes - 0 missing values
One of two multivariate regression data sets from paper industry, from an experiment at the paper plant Saugbruksforeningen, Norway. They have been described and analysed in: Aldrin, M. (1996),…
0 runs0 likes0 downloads0 reach5 impact
30 instances - 41 features - 0 classes - 0 missing values
This data set addresses a control problem, namely flying a F16 aircraft. The attributes describe the status of the aeroplane, while the goal is to predict the control action on the ailerons of the…
0 runs0 likes6 downloads6 reach5 impact
13750 instances - 41 features - 0 classes - 0 missing values
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…
0 runs0 likes0 downloads0 reach5 impact
22 instances - 40 features - 0 classes - 0 missing values
No data.
307 runs0 likes3 downloads3 reach2 impact
1000000 instances - 41 features - 3 classes - 0 missing values
####1. Summary This database was generated by the Laboratory of Image Processing and Pattern Recognition (INPG-LTIRF) in the development of the Esprit project ELENA No. 6891 and the Esprit working…
18284 runs0 likes11 downloads11 reach10 impact
5500 instances - 41 features - 11 classes - 0 missing values
__Major changes w.r.t. version 1: changed binary features to data type factor.__ Dataset from the Agnostic Learning vs. Prior Knowledge Challenge (http://www.agnostic.inf.ethz.ch), which consisted of…
0 runs0 likes0 downloads0 reach2 impact
14395 instances - 217 features - 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…
778 runs0 likes9 downloads9 reach7 impact
5000 instances - 41 features - 2 classes - 0 missing values
Generator generating 3 classes of waves. Each class is generated from a combination of 2 of 3 "base" waves. For details, see Breiman,L., Friedman,J.H., Olshen,R.A., and Stone,C.J. (1984).…
19670 runs1 likes53 downloads54 reach2 impact
5000 instances - 41 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…
602 runs0 likes12 downloads12 reach7 impact
13750 instances - 41 features - 2 classes - 0 missing values
Kung chi
1 runs0 likes4 downloads4 reach4 impact
123 instances - 40 features - 2 classes - 0 missing values
knugget chase 3
0 runs0 likes2 downloads2 reach4 impact
194 instances - 40 features - 2 classes - 0 missing values
Mind Cave 2
0 runs0 likes3 downloads3 reach3 impact
125 instances - 40 features - 2 classes - 0 missing values
One of the NASA Metrics Data Program defect data sets. The specific type of software is unknown. Data comes from McCabe and Halstead features extractors of source code. These features were defined in…
772 runs0 likes10 downloads10 reach7 impact
161 instances - 40 features - 2 classes - 0 missing values
One of the NASA Metrics Data Program defect data sets. The specific type of software is unknown. Data comes from McCabe and Halstead features extractors of source code. These features were defined in…
777 runs0 likes9 downloads9 reach7 impact
458 instances - 40 features - 2 classes - 0 missing values
Ask a home buyer to describe their dream house, and they probably won't begin with the height of the basement ceiling or the proximity to an east-west railroad. But this playground competition's…
0 runs0 likes0 downloads0 reach0 impact
1460 instances - 81 features - 0 classes - 6965 missing values
One of the NASA Metrics Data Program defect data sets. The specific type of software is unknown. Data comes from McCabe and Halstead features extractors of source code. These features were defined in…
815 runs0 likes14 downloads14 reach9 impact
9466 instances - 39 features - 2 classes - 0 missing values
pie chart 1
102 runs0 likes5 downloads5 reach5 impact
705 instances - 38 features - 2 classes - 0 missing values
pie chart 3
103 runs0 likes6 downloads6 reach5 impact
1077 instances - 38 features - 2 classes - 0 missing values
Mega watt
183 runs0 likes8 downloads8 reach7 impact
253 instances - 38 features - 2 classes - 0 missing values
Pizza cutter 3
188 runs0 likes6 downloads6 reach6 impact
1043 instances - 38 features - 2 classes - 0 missing values
Costa madre 1
90 runs0 likes6 downloads6 reach7 impact
296 instances - 38 features - 2 classes - 0 missing values
cast metal 1
111 runs0 likes8 downloads8 reach5 impact
327 instances - 38 features - 2 classes - 0 missing values
Mean While 1
0 runs0 likes3 downloads3 reach3 impact
253 instances - 38 features - 2 classes - 0 missing values
* Dataset Title: AutoUniv Dataset data problem: autoUniv-au6-250-drift-au6-cd1-500 * Abstract: AutoUniv is an advanced data generator for classifications tasks. The aim is to reflect the nuances and…
11011 runs0 likes9 downloads9 reach39 impact
750 instances - 41 features - 8 classes - 0 missing values
* Dataset Title: AutoUniv Dataset data problem: autoUniv-au6-cd1-400 * Abstract: AutoUniv is an advanced data generator for classifications tasks. The aim is to reflect the nuances and heterogeneity…
144 runs0 likes3 downloads3 reach5 impact
400 instances - 41 features - 8 classes - 0 missing values
* Dataset Title: AutoUniv Dataset data problem: autoUniv-au6-1000 * Abstract: AutoUniv is an advanced data generator for classifications tasks. The aim is to reflect the nuances and heterogeneity of…
11010 runs0 likes16 downloads16 reach39 impact
1000 instances - 41 features - 8 classes - 0 missing values
No data.
0 runs0 likes2 downloads2 reach1 impact
1000000 instances - 37 features - 0 classes - 0 missing values
Source: Ashwin Srinivasan Department of Statistics and Data Modeling University of Strathclyde Glasgow Scotland UK ross '@' uk.ac.turing The original Landsat data for this database was generated from…
1 runs1 likes6 downloads7 reach7 impact
6435 instances - 37 features - 0 classes - 0 missing values