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Mythbusting data mining urban legends through large scale experimentation

Mythbusting data mining urban legends through large scale experimentation

Created 24-07-2016 by Martijn Post Visibility: public
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No data.
697 runs0 likes0 downloads0 reach0 impact
320 instances - 9 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…
2862 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…
79 runs0 likes0 downloads0 reach0 impact
322 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…
2860 runs0 likes0 downloads0 reach0 impact
604 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
275 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…
76 runs0 likes0 downloads0 reach0 impact
187 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
484 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
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…
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…
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…
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
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…
2862 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…
2866 runs0 likes0 downloads0 reach0 impact
546 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
250 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
355 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
203 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
193 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
384 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…
2865 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
421 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
201 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…
82 runs0 likes0 downloads0 reach0 impact
405 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
413 instances - 10936 features - 2 classes - 0 missing values
Dataset from the MLRR repository: http://axon.cs.byu.edu:5000/
180 runs0 likes5 downloads5 reach24 impact
294 instances - 11 features - 2 classes - 0 missing values
Donated by P. Savicky, Institute of Computer Science, AS of CR, Czech Republic Methods for multidimensional event classification: a case study using images from a Cherenkov gamma-ray telescope.…
65383 runs0 likes0 downloads0 reach0 impact
19020 instances - 12 features - 2 classes - 0 missing values
Dataset from the MLRR repository: http://axon.cs.byu.edu:5000/
68 runs0 likes0 downloads0 reach0 impact
32561 instances - 16 features - 2 classes - 4262 missing values
Dataset from the MLRR repository: http://axon.cs.byu.edu:5000/ More infos: https://archive.ics.uci.edu/ml/datasets/Musk+(Version+2)
82516 runs0 likes0 downloads0 reach0 impact
6598 instances - 168 features - 2 classes - 0 missing values
Embryonal tumours of the central nervous system Prediction of Central Nervous System Embryonal Tumour Outcome based on Gene Expression. Nature, VOL 415, pp. 436-442, 24 January 2002. Scott L. Pomeroy,…
343 runs0 likes0 downloads0 reach0 impact
60 instances - 7130 features - 2 classes - 0 missing values
Molecular Classification of Cancer: Class Discovery and Class Prediction by Gene Expression Monitoring. Science, VOL 286, pp. 531-537, 15 October 1999. Web supplement to the article T.R. Golub, D. K.…
451 runs0 likes0 downloads0 reach0 impact
72 instances - 7130 features - 2 classes - 0 missing values
No data.
496 runs0 likes0 downloads0 reach0 impact
45 instances - 4027 features - 2 classes - 5948 missing values
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% This is a PROMISE Software Engineering Repository data set made publicly available in order to encourage repeatable,…
908 runs0 likes0 downloads0 reach0 impact
130 instances - 9 features - 2 classes - 0 missing values
No data.
748 runs0 likes0 downloads0 reach0 impact
274 instances - 9 features - 2 classes - 0 missing values
One of the NASA Metrics Data Program defect data sets. Data from flight software for earth orbiting satellite. Data comes from McCabe and Halstead features extractors of source code. These features…
875 runs0 likes0 downloads0 reach0 impact
5589 instances - 37 features - 2 classes - 0 missing values
One of the NASA Metrics Data Program defect data sets. Data from flight software for earth orbiting satellite. Data comes from McCabe and Halstead features extractors of source code. These features…
149998 runs0 likes27 downloads27 reach28 impact
1109 instances - 22 features - 2 classes - 0 missing values
One of the NASA Metrics Data Program defect data sets. Data from software for storage management for receiving and processing ground data. Data comes from McCabe and Halstead features extractors of…
161516 runs2 likes29 downloads31 reach30 impact
2109 instances - 22 features - 2 classes - 0 missing values
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% This is a PROMISE Software Engineering Repository data set made publicly available in order to encourage repeatable,…
765 runs0 likes0 downloads0 reach0 impact
145 instances - 95 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 likes0 downloads0 reach0 impact
458 instances - 40 features - 2 classes - 0 missing values
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %% This is a PROMISE Software Engineering Repository data set made publicly available in order to encourage repeatable,…
789 runs0 likes9 downloads9 reach14 impact
101 instances - 30 features - 2 classes - 0 missing values
No data.
726 runs0 likes0 downloads0 reach0 impact
36 instances - 30 features - 2 classes - 0 missing values
No data.
794 runs0 likes0 downloads0 reach0 impact
107 instances - 30 features - 2 classes - 0 missing values
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %% This is a PROMISE Software Engineering Repository data set made publicly available in order to encourage repeatable,…
756 runs0 likes8 downloads8 reach14 impact
121 instances - 30 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…
815 runs0 likes15 downloads15 reach18 impact
9466 instances - 39 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 likes0 downloads0 reach0 impact
161 instances - 40 features - 2 classes - 0 missing values
This is a PROMISE data set made publicly available in order to encourage repeatable, verifiable, refutable, and/or improvable predictive models of software engineering. If you publish material based…
21918 runs0 likes0 downloads0 reach0 impact
10885 instances - 22 features - 2 classes - 25 missing values
One of the NASA Metrics Data Program defect data sets. Data from flight software for earth orbiting satellite. Data comes from McCabe and Halstead features extractors of source code. These features…
146026 runs1 likes18 downloads19 reach27 impact
1563 instances - 38 features - 2 classes - 0 missing values
One of the NASA Metrics Data Program defect data sets. Data from flight software for earth orbiting satellite. Data comes from McCabe and Halstead features extractors of source code. These features…
115699 runs0 likes17 downloads17 reach28 impact
1458 instances - 38 features - 2 classes - 0 missing values
No data.
747 runs0 likes0 downloads0 reach0 impact
369 instances - 9 features - 2 classes - 0 missing values
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% This is a PROMISE Software Engineering Repository data set made publicly available in order to encourage repeatable,…
109967 runs0 likes0 downloads0 reach0 impact
15545 instances - 6 features - 2 classes - 0 missing values
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% This is a PROMISE Software Engineering Repository data set made publicly available in order to encourage repeatable,…
747 runs0 likes0 downloads0 reach0 impact
145 instances - 95 features - 2 classes - 0 missing values
Datasets from the Agnostic Learning vs. Prior Knowledge Challenge (http://www.agnostic.inf.ethz.ch) Dataset from: http://www.agnostic.inf.ethz.ch/datasets.php Modified by TunedIT (converted to ARFF…
548 runs0 likes0 downloads0 reach0 impact
3468 instances - 785 features - 2 classes - 0 missing values
Datasets from the Agnostic Learning vs. Prior Knowledge Challenge (http://www.agnostic.inf.ethz.ch) Dataset from: http://www.agnostic.inf.ethz.ch/datasets.php Modified by TunedIT (converted to ARFF…
486 runs0 likes0 downloads0 reach0 impact
14395 instances - 109 features - 2 classes - 0 missing values
Dataset from the Agnostic Learning vs. Prior Knowledge Challenge (http://www.agnostic.inf.ethz.ch), which consisted of 5 different datasets (SYLVA, GINA, NOVA, HIVA, ADA). The purpose of the challenge…
69235 runs0 likes0 downloads0 reach0 impact
3468 instances - 971 features - 2 classes - 0 missing values
Datasets from the Agnostic Learning vs. Prior Knowledge Challenge (http://www.agnostic.inf.ethz.ch) Dataset from: http://www.agnostic.inf.ethz.ch/datasets.php Modified by TunedIT (converted to ARFF…
778 runs0 likes0 downloads0 reach0 impact
4562 instances - 15 features - 2 classes - 88 missing values
Dataset from the Agnostic Learning vs. Prior Knowledge Challenge (http://www.agnostic.inf.ethz.ch), which consisted of 5 different datasets (SYLVA, GINA, NOVA, HIVA, ADA). The purpose of the challenge…
63189 runs0 likes0 downloads0 reach0 impact
14395 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…
728 runs0 likes0 downloads0 reach0 impact
2000 instances - 241 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…
781 runs0 likes0 downloads0 reach0 impact
5473 instances - 11 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…
794 runs0 likes9 downloads9 reach15 impact
2000 instances - 65 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…
676 runs0 likes0 downloads0 reach0 impact
10992 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…
774 runs0 likes0 downloads0 reach0 impact
797 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…
140 runs0 likes0 downloads0 reach0 impact
194 instances - 29 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…
815 runs0 likes0 downloads0 reach0 impact
336 instances - 8 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…
732 runs0 likes0 downloads0 reach0 impact
63 instances - 32 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…
104 runs0 likes0 downloads0 reach0 impact
379 instances - 8 features - 2 classes - 1368 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…
103 runs0 likes0 downloads0 reach0 impact
107 instances - 12 features - 2 classes - 71 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…
748 runs0 likes0 downloads0 reach0 impact
148 instances - 19 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…
772 runs0 likes0 downloads0 reach0 impact
214 instances - 10 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…
169 runs0 likes0 downloads0 reach0 impact
600 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…
752 runs0 likes0 downloads0 reach0 impact
339 instances - 18 features - 2 classes - 225 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…
733 runs0 likes0 downloads0 reach0 impact
7485 instances - 56 features - 2 classes - 32427 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…
106 runs0 likes0 downloads0 reach0 impact
76 instances - 45 features - 2 classes - 22 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…
737 runs0 likes0 downloads0 reach0 impact
3772 instances - 30 features - 2 classes - 6064 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
226 instances - 70 features - 2 classes - 317 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…
104 runs0 likes0 downloads0 reach0 impact
57 instances - 11 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…
777 runs0 likes0 downloads0 reach0 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…
792 runs0 likes0 downloads0 reach0 impact
214 instances - 10 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…
792 runs0 likes8 downloads8 reach15 impact
2000 instances - 48 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…
810 runs0 likes0 downloads0 reach0 impact
846 instances - 19 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…
744 runs0 likes0 downloads0 reach0 impact
7019 instances - 61 features - 2 classes - 43814 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…
119 runs0 likes0 downloads0 reach0 impact
95 instances - 9 features - 2 classes - 9 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…
765 runs0 likes0 downloads0 reach0 impact
1728 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…
712 runs0 likes0 downloads0 reach0 impact
898 instances - 39 features - 2 classes - 22175 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…
700 runs0 likes0 downloads0 reach0 impact
67 instances - 16 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…
141 runs0 likes0 downloads0 reach0 impact
500 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…
736 runs0 likes0 downloads0 reach0 impact
364 instances - 33 features - 2 classes - 80 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…
687 runs0 likes0 downloads0 reach0 impact
52 instances - 24 features - 2 classes - 39 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 likes0 downloads0 reach0 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…
736 runs0 likes0 downloads0 reach0 impact
1473 instances - 10 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
303 instances - 14 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…
622 runs0 likes0 downloads0 reach0 impact
10108 instances - 69 features - 2 classes - 2699 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…
765 runs0 likes0 downloads0 reach0 impact
5620 instances - 65 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…
778 runs0 likes0 downloads0 reach0 impact
5000 instances - 41 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…
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…
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…
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…
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…
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…
1136 runs0 likes0 downloads0 reach0 impact
150 instances - 5 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). The multi-class target feature is converted to a two-class nominal target feature by re-labeling the majority class as positive ('P') and…
708 runs0 likes0 downloads0 reach0 impact
365 instances - 4 features - 2 classes - 30 missing values