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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 likes4 downloads4 reach8 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 likes15 downloads15 reach18 impact
9466 instances - 39 features - 2 classes - 0 missing values
Kung chi
1 runs0 likes4 downloads4 reach12 impact
123 instances - 40 features - 2 classes - 0 missing values
knugget chase 3
0 runs0 likes2 downloads2 reach12 impact
194 instances - 40 features - 2 classes - 0 missing values
Mind Cave 2
0 runs0 likes3 downloads3 reach11 impact
125 instances - 40 features - 2 classes - 0 missing values
One of the NASA Metrics Data Program defect data sets. Data from software for science data processing. Data comes from McCabe and Halstead features extractors of source code. These features were…
777 runs0 likes9 downloads9 reach15 impact
458 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 reach15 impact
161 instances - 40 features - 2 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 reach10 impact
14395 instances - 217 features - classes - 0 missing values
No data.
307 runs0 likes3 downloads3 reach11 impact
1000000 instances - 41 features - 3 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 reach13 impact
22 instances - 40 features - 0 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…
20229 runs0 likes13 downloads13 reach18 impact
5500 instances - 41 features - 11 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).…
19675 runs1 likes53 downloads54 reach12 impact
5000 instances - 41 features - 3 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 reach15 impact
5000 instances - 41 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…
602 runs1 likes12 downloads13 reach15 impact
13750 instances - 41 features - 2 classes - 0 missing values
No data.
0 runs0 likes0 downloads0 reach9 impact
1000000 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 reach14 impact
13750 instances - 41 features - 0 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). *…
267507 runs1 likes23 downloads24 reach28 impact
1055 instances - 42 features - 2 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 reach13 impact
30 instances - 41 features - 0 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…
37 runs0 likes1 downloads1 reach21 impact
959 instances - 45 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 likes3 downloads3 reach12 impact
267 instances - 45 features - 2 classes - 0 missing values
No data.
43 runs0 likes2 downloads2 reach9 impact
1000000 instances - 45 features - 2 classes - 0 missing values
No data.
47 runs0 likes1 downloads1 reach9 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…
1103 runs0 likes12 downloads12 reach15 impact
349 instances - 45 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…
729 runs0 likes9 downloads9 reach14 impact
45 instances - 47 features - 2 classes - 0 missing values
No data.
52 runs0 likes3 downloads3 reach11 impact
1000000 instances - 48 features - 10 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…
34558 runs0 likes23 downloads23 reach12 impact
2000 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 reach15 impact
2000 instances - 48 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 reach11 impact
45 instances - 47 features - classes - 0 missing values
sd vfv
0 runs0 likes0 downloads0 reach7 impact
4 instances - 50 features - 2 classes - 0 missing values
r rg
0 runs0 likes0 downloads0 reach8 impact
4 instances - 50 features - classes - 0 missing values
dd ref
0 runs0 likes0 downloads0 reach7 impact
4 instances - 50 features - classes - 0 missing values
ef f
0 runs0 likes0 downloads0 reach7 impact
4 instances - 49 features - classes - 0 missing values
rrvrf 4rr
0 runs0 likes0 downloads0 reach7 impact
4 instances - 49 features - 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…
1 runs0 likes1 downloads1 reach16 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 reach15 impact
15000 instances - 49 features - 2 classes - 0 missing values
efe def
0 runs0 likes0 downloads0 reach8 impact
4 instances - 49 features - 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 likes4 downloads4 reach11 impact
15000 instances - 49 features - 0 classes - 0 missing values
Oil dataset
204 runs3 likes19 downloads22 reach25 impact
937 instances - 50 features - 2 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…
12 runs0 likes4 downloads4 reach13 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…
620 runs0 likes10 downloads10 reach15 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…
772 runs0 likes7 downloads7 reach15 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 reach15 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…
773 runs0 likes6 downloads6 reach14 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…
764 runs0 likes6 downloads6 reach14 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 reach15 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…
766 runs0 likes7 downloads7 reach14 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…
646 runs0 likes9 downloads9 reach15 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…
781 runs0 likes8 downloads8 reach15 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…
786 runs0 likes6 downloads6 reach15 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…
755 runs0 likes6 downloads6 reach15 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…
636 runs0 likes8 downloads8 reach15 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…
614 runs0 likes9 downloads9 reach15 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…
801 runs0 likes9 downloads9 reach15 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…
748 runs0 likes6 downloads6 reach15 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…
784 runs0 likes7 downloads7 reach15 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…
621 runs0 likes8 downloads8 reach15 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…
775 runs0 likes6 downloads6 reach15 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…
788 runs0 likes7 downloads7 reach14 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…
810 runs0 likes6 downloads6 reach14 impact
100 instances - 51 features - 2 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…
26323 runs1 likes21 downloads22 reach43 impact
6118 instances - 52 features - 6 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 reach13 impact
14 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 reach13 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 reach13 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 reach13 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 reach13 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 reach13 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 reach13 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 reach13 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 reach13 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 reach13 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 reach13 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 reach13 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 reach13 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 reach13 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 reach13 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 reach13 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 reach13 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 likes2 downloads2 reach13 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 reach13 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 reach13 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 reach13 impact
250 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 reach13 impact
31 instances - 54 features - 0 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…
12 runs0 likes1 downloads1 reach18 impact
83733 instances - 55 features - 4 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 likes9 downloads9 reach15 impact
581012 instances - 55 features - 2 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…
161528 runs5 likes89 downloads94 reach12 impact
4601 instances - 58 features - 2 classes - 0 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 reach27 impact
2500 instances - 101 features - 3 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…
28060 runs19 likes162 downloads181 reach34 impact
8378 instances - 123 features - 2 classes - 18372 missing values
This dataset summarizes a heterogeneous set of features about articles published by Mashable in a period of two years. The goal is to predict the number of shares in social networks (popularity). *…
0 runs0 likes5 downloads5 reach11 impact
39644 instances - 61 features - 0 classes - 0 missing values
Test dataset
3 runs0 likes0 downloads0 reach15 impact
15547 instances - 61 features - 2 classes - 280 missing values
No data.
296 runs0 likes7 downloads7 reach9 impact
1000000 instances - 61 features - 2 classes - 0 missing values
Version with url set as row id, creator data missing due to bad formatting.**Author**: Kelwin Fernandes (INESC TEC, Universidade doPorto), Pedro Vinagre (ALGORITMI Research Centre, Universidade do…
0 runs0 likes0 downloads0 reach0 impact
39644 instances - 60 features - 0 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 reach16 impact
416188 instances - 61 features - 355 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 likes25 downloads26 reach9 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 reach15 impact
186 instances - 61 features - 2 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…
20355 runs0 likes10 downloads10 reach50 impact
600 instances - 61 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 reach16 impact
600 instances - 61 features - 2 classes - 0 missing values
libSVM","AAD group #Dataset from the LIBSVM data repository. Preprocessing: scaled to [-1,1]
0 runs0 likes0 downloads0 reach16 impact
3175 instances - 61 features - 0 classes - 0 missing values
Test dataset
0 runs0 likes1 downloads1 reach13 impact
15547 instances - 61 features - 0 classes - 280 missing values
Test dataset
0 runs0 likes1 downloads1 reach13 impact
15547 instances - 61 features - 0 classes - 280 missing values
Test dataset
0 runs0 likes0 downloads0 reach13 impact
15547 instances - 61 features - 0 classes - 280 missing values