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…
119 runs0 likes0 downloads0 reach0 impact
50 instances - 6 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…
103 runs0 likes0 downloads0 reach0 impact
92 instances - 10 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…
1034 runs0 likes0 downloads0 reach0 impact
100 instances - 7 features - 2 classes - 0 missing values
Dataset from `Pattern Recognition and Neural Networks' by B.D. Ripley. Cambridge University Press (1996) ISBN 0-521-46086-7. The background to the datasets is described in section 1.4; this file…
1105 runs0 likes0 downloads0 reach0 impact
250 instances - 3 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…
698 runs0 likes0 downloads0 reach0 impact
97 instances - 11 features - 2 classes - 0 missing values
Schizophrenic Eye-Tracking Data in Rubin and Wu (1997) Biometrics. Yingnian Wu (wu@hustat.harvard.edu) [14/Oct/97] Information about the dataset CLASSTYPE: nominal CLASSINDEX: last
748 runs0 likes0 downloads0 reach0 impact
340 instances - 15 features - 2 classes - 834 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…
103 runs0 likes0 downloads0 reach0 impact
52 instances - 9 features - 2 classes - 0 missing values
PRO FOOTBALL SCORES (raw data appears after the description below) How well do the oddsmakers of Las Vegas predict the outcome of professional football games? Is there really a home field advantage -…
16080 runs0 likes0 downloads0 reach0 impact
672 instances - 10 features - 2 classes - 1200 missing values
analcatdata A collection of data sets used in the book "Analyzing Categorical Data," by Jeffrey S. Simonoff, Springer-Verlag, New York, 2003. The submission consists of a zip file containing two…
1030 runs0 likes0 downloads0 reach0 impact
132 instances - 4 features - 2 classes - 0 missing values
Datasets for `Pattern Recognition and Neural Networks' by B.D. Ripley ===================================================================== Cambridge University Press (1996) ISBN 0-521-46086-7 The…
743 runs0 likes0 downloads0 reach0 impact
200 instances - 8 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…
1116 runs0 likes0 downloads0 reach0 impact
120 instances - 4 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 likes0 downloads0 reach0 impact
264 instances - 5 features - 2 classes - 0 missing values
February 23, 1982 The 1982 annual meetings of the American Statistical Association (ASA) will be held August 16-19, 1982 in Cincinnati. At that meeting, the ASA Committee on Statistical Graphics plans…
759 runs0 likes0 downloads0 reach0 impact
209 instances - 9 features - 2 classes - 15 missing values
### Description Cylinder bands UCI dataset - Process delays known as cylinder banding in rotogravure printing were substantially mitigated using control rules discovered by decision tree induction.…
0 runs0 likes0 downloads0 reach0 impact
540 instances - 38 features - 2 classes - 999 missing values
### Description Cylinder bands UCI dataset - Process delays known as cylinder banding in rotogravure printing were substantially mitigated using control rules discovered by decision tree induction.…
0 runs0 likes0 downloads0 reach0 impact
540 instances - 38 features - 2 classes - 999 missing values
### Description Cylinder bands UCI dataset - Process delays known as cylinder banding in rotogravure printing were substantially mitigated using control rules discovered by decision tree induction.…
0 runs0 likes0 downloads0 reach0 impact
540 instances - 38 features - 2 classes - 999 missing values
Date: Tue, 15 Nov 88 15:44:08 EST From: stan To: aha@ICS.UCI.EDU 1. Title: Final settlements in labor negotitions in Canadian industry 2. Source Information -- Creators:…
7681 runs0 likes17 downloads17 reach13 impact
57 instances - 17 features - 2 classes - 326 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…
686 runs0 likes0 downloads0 reach0 impact
782 instances - 9 features - 2 classes - 466 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 likes0 downloads0 reach0 impact
205 instances - 26 features - 2 classes - 57 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 likes0 downloads0 reach0 impact
950 instances - 10 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…
705 runs0 likes0 downloads0 reach0 impact
398 instances - 8 features - 2 classes - 6 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…
759 runs0 likes0 downloads0 reach0 impact
250 instances - 26 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…
744 runs0 likes0 downloads0 reach0 impact
8192 instances - 33 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…
734 runs0 likes0 downloads0 reach0 impact
506 instances - 14 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
672 runs0 likes0 downloads0 reach0 impact
158 instances - 8 features - 2 classes - 87 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
763 runs0 likes0 downloads0 reach0 impact
250 instances - 101 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 likes0 downloads0 reach0 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…
723 runs0 likes0 downloads0 reach0 impact
34 instances - 9 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
745 runs0 likes0 downloads0 reach0 impact
240 instances - 125 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…
720 runs0 likes0 downloads0 reach0 impact
159 instances - 10 features - 2 classes - 6 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…
754 runs0 likes0 downloads0 reach0 impact
38 instances - 6 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
608 runs1 likes9 downloads10 reach15 impact
1000 instances - 26 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 likes0 downloads0 reach0 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…
683 runs0 likes0 downloads0 reach0 impact
60 instances - 11 features - 2 classes - 14 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…
589 runs0 likes0 downloads0 reach0 impact
22784 instances - 9 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
708 runs0 likes0 downloads0 reach0 impact
286 instances - 10 features - 2 classes - 9 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…
625 runs0 likes0 downloads0 reach0 impact
1000 instances - 11 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…
1176 runs0 likes0 downloads0 reach0 impact
16599 instances - 19 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…
760 runs0 likes0 downloads0 reach0 impact
6574 instances - 15 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…
771 runs0 likes0 downloads0 reach0 impact
500 instances - 26 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…
135 runs0 likes0 downloads0 reach0 impact
3190 instances - 61 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…
143 runs0 likes0 downloads0 reach0 impact
531 instances - 102 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…
1032 runs0 likes0 downloads0 reach0 impact
151 instances - 6 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…
857 runs0 likes0 downloads0 reach0 impact
9961 instances - 15 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…
639 runs0 likes0 downloads0 reach0 impact
20000 instances - 17 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…
766 runs0 likes0 downloads0 reach0 impact
2000 instances - 217 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…
176 runs0 likes0 downloads0 reach0 impact
101 instances - 17 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…
131 runs0 likes0 downloads0 reach0 impact
1340 instances - 17 features - 2 classes - 20 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…
718 runs0 likes0 downloads0 reach0 impact
406 instances - 9 features - 2 classes - 14 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…
173 runs0 likes0 downloads0 reach0 impact
106 instances - 58 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…
721 runs0 likes0 downloads0 reach0 impact
412 instances - 9 features - 2 classes - 96 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…
772 runs0 likes0 downloads0 reach0 impact
2310 instances - 20 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…
801 runs0 likes0 downloads0 reach0 impact
841 instances - 71 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…
758 runs0 likes11 downloads11 reach15 impact
2000 instances - 77 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…
707 runs0 likes0 downloads0 reach0 impact
52 instances - 25 features - 2 classes - 7 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…
652 runs0 likes0 downloads0 reach0 impact
12960 instances - 9 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…
717 runs0 likes0 downloads0 reach0 impact
90 instances - 9 features - 2 classes - 3 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…
722 runs0 likes0 downloads0 reach0 impact
285 instances - 8 features - 2 classes - 27 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…
780 runs0 likes0 downloads0 reach0 impact
178 instances - 14 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…
1139 runs0 likes0 downloads0 reach0 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…
727 runs0 likes0 downloads0 reach0 impact
205 instances - 26 features - 2 classes - 59 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…
773 runs0 likes0 downloads0 reach0 impact
2000 instances - 7 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…
688 runs0 likes0 downloads0 reach0 impact
294 instances - 14 features - 2 classes - 782 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…
698 runs0 likes0 downloads0 reach0 impact
36 instances - 23 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…
708 runs0 likes0 downloads0 reach0 impact
365 instances - 4 features - 2 classes - 30 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 likes0 downloads0 reach0 impact
150 instances - 5 features - 2 classes - 0 missing values
GEMLeR provides a collection of gene expression datasets that can be used for benchmarking gene expression oriented machine learning algorithms. They can be used for estimation of different quality…
78 runs0 likes0 downloads0 reach0 impact
130 instances - 10936 features - 2 classes - 0 missing values
GEMLeR provides a collection of gene expression datasets that can be used for benchmarking gene expression oriented machine learning algorithms. They can be used for estimation of different quality…
72 runs0 likes0 downloads0 reach0 impact
1545 instances - 10936 features - 2 classes - 0 missing values
GEMLeR provides a collection of gene expression datasets that can be used for benchmarking gene expression oriented machine learning algorithms. They can be used for estimation of different quality…
78 runs0 likes0 downloads0 reach0 impact
363 instances - 10936 features - 2 classes - 0 missing values
GEMLeR provides a collection of gene expression datasets that can be used for benchmarking gene expression oriented machine learning algorithms. They can be used for estimation of different quality…
77 runs0 likes0 downloads0 reach0 impact
329 instances - 10936 features - 2 classes - 0 missing values
GEMLeR provides a collection of gene expression datasets that can be used for benchmarking gene expression oriented machine learning algorithms. They can be used for estimation of different quality…
59 runs0 likes0 downloads0 reach0 impact
1545 instances - 10937 features - 2 classes - 0 missing values
GEMLeR provides a collection of gene expression datasets that can be used for benchmarking gene expression oriented machine learning algorithms. They can be used for estimation of different quality…
77 runs0 likes0 downloads0 reach0 impact
337 instances - 10936 features - 2 classes - 0 missing values
GEMLeR provides a collection of gene expression datasets that can be used for benchmarking gene expression oriented machine learning algorithms. They can be used for estimation of different quality…
65 runs0 likes0 downloads0 reach0 impact
468 instances - 10937 features - 2 classes - 0 missing values
GEMLeR provides a collection of gene expression datasets that can be used for benchmarking gene expression oriented machine learning algorithms. They can be used for estimation of different quality…
67 runs0 likes0 downloads0 reach0 impact
458 instances - 10936 features - 2 classes - 0 missing values
GEMLeR provides a collection of gene expression datasets that can be used for benchmarking gene expression oriented machine learning algorithms. They can be used for estimation of different quality…
65 runs0 likes0 downloads0 reach0 impact
470 instances - 10936 features - 2 classes - 0 missing values
GEMLeR provides a collection of gene expression datasets that can be used for benchmarking gene expression oriented machine learning algorithms. They can be used for estimation of different quality…
65 runs0 likes0 downloads0 reach0 impact
138 instances - 10936 features - 2 classes - 0 missing values
GEMLeR provides a collection of gene expression datasets that can be used for benchmarking gene expression oriented machine learning algorithms. They can be used for estimation of different quality…
2841 runs0 likes0 downloads0 reach0 impact
630 instances - 10936 features - 2 classes - 0 missing values
GEMLeR provides a collection of gene expression datasets that can be used for benchmarking gene expression oriented machine learning algorithms. They can be used for estimation of different quality…
65 runs0 likes0 downloads0 reach0 impact
324 instances - 10937 features - 2 classes - 0 missing values
No data.
353 runs0 likes0 downloads0 reach0 impact
120919 instances - 1002 features - 2 classes - 0 missing values
Vehicle classification in distributed sensor networks. Journal of Parallel and Distributed Computing, 64(7):826-838, July 2004. This is the SensIT Vehicle (combined) dataset, retrieved 2013-11-14 from…
403 runs0 likes0 downloads0 reach0 impact
98528 instances - 101 features - 2 classes - 0 missing values
Yeast dataset Past Usage: André Elisseeff and Jason Weston. A kernel method for multi-labelled classification. In Thomas G. Dietterich, Susan Becker, and Zoubin Ghahramani, editors, Advances in…
139 runs0 likes0 downloads0 reach0 impact
2417 instances - 117 features - 2 classes - 0 missing values
Fast training of support vector machines using sequential minimal optimization. In Bernhard Schölkopf, Christopher J. C. Burges, and Alexander J. Smola, editors, Advances in Kernel Methods - Support…
564 runs0 likes0 downloads0 reach0 impact
36974 instances - 124 features - 2 classes - 0 missing values
Andrew V Uzilov, Joshua M Keegan, and David H Mathews. Detection of non-coding RNAs on the basis of predicted secondary structure formation free energy change. BMC Bioinformatics, 7(173), 2006. This…
31 runs0 likes0 downloads0 reach0 impact
488565 instances - 9 features - 2 classes - 0 missing values
This is the poker dataset, retrieved 2013-11-14 from the libSVM site. Additional to the preprocessing done there (see LibSVM site for details), this dataset was created as follows: -join test and…
23 runs0 likes0 downloads0 reach0 impact
1025010 instances - 11 features - 2 classes - 0 missing values
Data originating from the book "Analyzing Categorical Data" by Jeffrey S. Simonoff.
1087 runs0 likes0 downloads0 reach0 impact
50 instances - 5 features - 2 classes - 0 missing values
SPECT 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. Sources: --…
1296 runs0 likes0 downloads0 reach0 impact
267 instances - 23 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 likes0 downloads0 reach0 impact
349 instances - 45 features - 2 classes - 0 missing values
This database contains the HTML source of web pages plus the ratings of a single user on these web pages. The web pages are on four separate subjects (Bands- recording artists; Goats; Sheep; and…
0 runs0 likes0 downloads0 reach0 impact
65 instances - 3 features - 2 classes - 0 missing values
Once upon a time, in July 1991, the monks of Corsendonk Priory were faced with a school held in their priory, namely the 2nd European Summer School on Machine Learning. After listening more than one…
358834 runs0 likes0 downloads0 reach0 impact
556 instances - 7 features - 2 classes - 0 missing values
Once upon a time, in July 1991, the monks of Corsendonk Priory were faced with a school held in their priory, namely the 2nd European Summer School on Machine Learning. After listening more than one…
394951 runs3 likes34 downloads37 reach39 impact
601 instances - 7 features - 2 classes - 0 missing values
Once upon a time, in July 1991, the monks of Corsendonk Priory were faced with a school held in their priory, namely the 2nd European Summer School on Machine Learning. After listening more than one…
108820 runs0 likes0 downloads0 reach0 impact
554 instances - 7 features - 2 classes - 0 missing values
Contains 110 data sets from the book 'The Statistical Sleuth' by Fred Ramsey and Dan Schafer; Duxbury Press, 1997. (schafer@stat.orst.edu) [14/Oct/97] (172k) Note: description taken from this web…
668 runs0 likes0 downloads0 reach0 impact
87 instances - 11 features - 2 classes - 0 missing values
Contains 110 data sets from the book 'The Statistical Sleuth' by Fred Ramsey and Dan Schafer; Duxbury Press, 1997. (schafer@stat.orst.edu) [14/Oct/97] (172k) Note: description taken from this web…
722 runs0 likes0 downloads0 reach0 impact
60 instances - 8 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…
691 runs0 likes0 downloads0 reach0 impact
528 instances - 22 features - 2 classes - 504 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…
102 runs0 likes0 downloads0 reach0 impact
67 instances - 15 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…
107 runs0 likes0 downloads0 reach0 impact
66 instances - 12 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
853 runs0 likes0 downloads0 reach0 impact
250 instances - 6 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
737 runs0 likes0 downloads0 reach0 impact
47 instances - 8 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 likes0 downloads0 reach0 impact
252 instances - 15 features - 2 classes - 0 missing values