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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…
587 runs0 likes5 downloads5 reach14 impact
61 instances - 19 features - 4 classes - 0 missing values
This S dump contains 22 data sets from the book Visualizing Data published by Hobart Press (books@hobart.com). The dump was created by data.dump() and can be read back into S by data.restore(). The…
899 runs0 likes8 downloads8 reach14 impact
130 instances - 3 features - 5 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 likes6 downloads6 reach14 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 likes6 downloads6 reach14 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…
792 runs0 likes7 downloads7 reach14 impact
100 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…
759 runs0 likes6 downloads6 reach14 impact
50 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…
1190 runs0 likes9 downloads9 reach14 impact
111 instances - 4 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
707 runs0 likes6 downloads6 reach14 impact
96 instances - 5 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
734 runs0 likes6 downloads6 reach14 impact
74 instances - 28 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…
119 runs0 likes7 downloads7 reach14 impact
50 instances - 4 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 likes5 downloads5 reach14 impact
130 instances - 10 features - 2 classes - 97 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…
767 runs0 likes9 downloads9 reach14 impact
76 instances - 7 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…
762 runs0 likes6 downloads6 reach14 impact
88 instances - 3 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 likes7 downloads7 reach14 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…
698 runs0 likes5 downloads5 reach14 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…
688 runs0 likes4 downloads4 reach14 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…
717 runs0 likes5 downloads5 reach14 impact
90 instances - 9 features - 2 classes - 3 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…
736 runs0 likes5 downloads5 reach14 impact
92 instances - 6 features - 2 classes - 26 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…
1038 runs0 likes9 downloads9 reach14 impact
147 instances - 7 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 likes4 downloads4 reach14 impact
54 instances - 8 features - 2 classes - 120 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…
514 runs0 likes7 downloads7 reach14 impact
130 instances - 2 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…
123 runs0 likes6 downloads6 reach14 impact
46 instances - 4 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…
114 runs0 likes5 downloads5 reach14 impact
42 instances - 16 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…
116 runs0 likes6 downloads6 reach14 impact
70 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…
640 runs0 likes6 downloads6 reach14 impact
214 instances - 10 features - 6 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…
731 runs0 likes5 downloads5 reach14 impact
93 instances - 7 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…
120 runs0 likes5 downloads5 reach14 impact
50 instances - 7 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…
728 runs0 likes6 downloads6 reach14 impact
61 instances - 3 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…
808 runs1 likes9 downloads10 reach14 impact
100 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…
789 runs0 likes8 downloads8 reach14 impact
73 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…
780 runs0 likes7 downloads7 reach14 impact
66 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…
1088 runs0 likes8 downloads8 reach14 impact
132 instances - 4 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…
115 runs0 likes5 downloads5 reach14 impact
40 instances - 2 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…
1173 runs0 likes8 downloads8 reach14 impact
100 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…
754 runs0 likes10 downloads10 reach14 impact
60 instances - 16 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…
985 runs0 likes8 downloads8 reach14 impact
100 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…
1268 runs0 likes11 downloads11 reach14 impact
131 instances - 4 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…
1252 runs0 likes9 downloads9 reach14 impact
130 instances - 3 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…
1202 runs0 likes9 downloads9 reach14 impact
100 instances - 4 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…
119 runs0 likes6 downloads6 reach14 impact
39 instances - 3 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…
112 runs0 likes5 downloads5 reach14 impact
42 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…
810 runs0 likes6 downloads6 reach14 impact
100 instances - 51 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 likes5 downloads5 reach14 impact
52 instances - 25 features - 2 classes - 7 missing values
This data set contains unweighted PUMS census data from the Los Angeles and Long Beach areas for the years 1970, 1980, and 1990. The coding schemes have been standardized (by the IPUMS project) to be…
434 runs0 likes10 downloads10 reach14 impact
7019 instances - 61 features - 8 classes - 48089 missing values
This data set contains unweighted PUMS census data from the Los Angeles and Long Beach areas for the years 1970, 1980, and 1990. The coding schemes have been standardized (by the IPUMS project) to be…
366 runs0 likes10 downloads10 reach14 impact
8844 instances - 61 features - 7 classes - 51515 missing values
This data set contains unweighted PUMS census data from the Los Angeles and Long Beach areas for the years 1970, 1980, and 1990. The coding schemes have been standardized (by the IPUMS project) to be…
354 runs0 likes7 downloads7 reach14 impact
7485 instances - 61 features - 7 classes - 52048 missing values
1. Title: Class-level data for KC1 This one includes a {_TRUE,FALSE} attribute (DL) to indicate defectiveness. 2. Sources (a) Creator: A. Gunes Koru (b) Date: February 21, 2005 (c) Contact: gkoru AT…
765 runs0 likes7 downloads7 reach14 impact
145 instances - 95 features - 2 classes - 0 missing values
1. Title/Topic : CM1/Baselines in Requirements Tracing 2. Sources: --Creators:NASA, then the NASA Metrics Data Program, -- http://mdp.ivv.nasa.gov. Contacts: Mike Chapman, Galaxy Global Corporation…
697 runs0 likes5 downloads5 reach14 impact
89 instances - 9 features - 2 classes - 0 missing values
County data from the 2000 Presidential Election in Florida. Compiled by Brett Presnell\ Department of Statistics, University of Florida These data are derived from three sources, described below. As…
32 runs0 likes4 downloads4 reach14 impact
67 instances - 16 features - 5 classes - 0 missing values
A collection of data sets used in the book "Analyzing Categorical Data," by Jeffrey S. Simonoff, Springer-Verlag, New York, 2003. Further details concerning the book, including information on…
119 runs0 likes5 downloads5 reach14 impact
50 instances - 6 features - 2 classes - 0 missing values
A collection of data sets used in the book "Analyzing Categorical Data," by Jeffrey S. Simonoff, Springer-Verlag, New York, 2003. Further details concerning the book, including information on…
581 runs0 likes5 downloads5 reach14 impact
400 instances - 6 features - 4 classes - 0 missing values
87 persons with lupus nephritis. Followed up 15+ years. 35 deaths. Var = duration of disease. Over 40 baseline variables avaiable from authors. For description of this data set arising from 87 persons…
737 runs0 likes10 downloads10 reach14 impact
87 instances - 4 features - 2 classes - 0 missing values
``` ITEM 1 = BUSINESS CONDIDIONS 6 MONTHS FROM NOW (CONFERENCE BOARD) ITEM 2 = JOBS 6 MONTHS FROM NOW (CONFERENCE BOARD) ITEM 3 = FAMILY INCOME 6 MONTHS FROM NOW (CONFERENCE BOARD) ITEM 4 = BUSINESS…
560 runs0 likes4 downloads4 reach14 impact
72 instances - 4 features - 6 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…
102 runs0 likes4 downloads4 reach14 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…
100 runs0 likes3 downloads3 reach14 impact
31 instances - 16 features - 2 classes - 150 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…
984 runs0 likes8 downloads8 reach14 impact
100 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…
683 runs0 likes5 downloads5 reach14 impact
60 instances - 11 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…
141 runs0 likes7 downloads7 reach14 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…
119 runs0 likes4 downloads4 reach14 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…
700 runs0 likes5 downloads5 reach14 impact
67 instances - 16 features - 2 classes - 0 missing values
### Yeast dataset . A kernel method for multi-labelled classification. This dataset contains micro-array expressions and phylogenetic profiles for 2417 yeast genes. Each gen is annotated with a subset…
139 runs0 likes8 downloads8 reach14 impact
2417 instances - 117 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…
965 runs0 likes9 downloads9 reach14 impact
137 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…
1043 runs0 likes10 downloads10 reach14 impact
125 instances - 5 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
766 runs0 likes7 downloads7 reach14 impact
100 instances - 51 features - 2 classes - 0 missing values
DATA-SETS FROM DIGGLE, P.J. (1990). TIME SERIES : A BIOSTATISTICAL INTRODUCTION. Oxford University Press. Table: Table A2 Wool prices Information about the dataset CLASSTYPE: numeric CLASSINDEX: none…
626 runs0 likes6 downloads6 reach14 impact
310 instances - 9 features - 9 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…
111 runs0 likes5 downloads5 reach14 impact
52 instances - 3 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…
1073 runs0 likes10 downloads10 reach14 impact
140 instances - 4 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…
789 runs0 likes7 downloads7 reach14 impact
100 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…
737 runs0 likes5 downloads5 reach14 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…
740 runs0 likes5 downloads5 reach14 impact
51 instances - 7 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…
1024 runs0 likes8 downloads8 reach14 impact
100 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…
1823 runs0 likes9 downloads9 reach14 impact
120 instances - 3 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 likes7 downloads7 reach14 impact
100 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…
1119 runs0 likes8 downloads8 reach14 impact
100 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…
106 runs0 likes5 downloads5 reach14 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…
104 runs0 likes3 downloads3 reach14 impact
57 instances - 11 features - 2 classes - 1 missing values
A collection of data sets used in the book "Analyzing Categorical Data," by Jeffrey S. Simonoff, Springer-Verlag, New York, 2003. Further details concerning the book, including information on…
50 runs0 likes5 downloads5 reach14 impact
95 instances - 8 features - 5 classes - 9 missing values
A collection of data sets used in the book "Analyzing Categorical Data," by Jeffrey S. Simonoff, Springer-Verlag, New York, 2003. Further details concerning the book, including information on…
1030 runs0 likes8 downloads8 reach14 impact
132 instances - 4 features - 2 classes - 0 missing values
A collection of data sets used in the book "Analyzing Categorical Data," by Jeffrey S. Simonoff, Springer-Verlag, New York, 2003. Further details concerning the book, including information on…
1116 runs0 likes9 downloads9 reach14 impact
120 instances - 4 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…
703 runs0 likes6 downloads6 reach14 impact
44 instances - 4 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…
1111 runs0 likes9 downloads9 reach14 impact
100 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…
455 runs0 likes5 downloads5 reach14 impact
108 instances - 4 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…
770 runs0 likes8 downloads8 reach14 impact
100 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…
730 runs0 likes5 downloads5 reach14 impact
93 instances - 23 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…
572 runs0 likes6 downloads6 reach14 impact
100 instances - 3 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 likes3 downloads3 reach14 impact
74 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…
733 runs0 likes4 downloads4 reach14 impact
87 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…
721 runs0 likes5 downloads5 reach14 impact
60 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…
687 runs0 likes5 downloads5 reach14 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…
103 runs0 likes5 downloads5 reach14 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…
732 runs0 likes5 downloads5 reach14 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…
748 runs0 likes8 downloads8 reach14 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 likes8 downloads8 reach14 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…
1149 runs0 likes10 downloads10 reach14 impact
138 instances - 3 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 likes7 downloads7 reach14 impact
132 instances - 5 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). The multi-class target feature is converted to a two-class nominal target feature by re-labeling the majority class as positive ('P') and…
746 runs0 likes7 downloads7 reach14 impact
72 instances - 4 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 likes7 downloads7 reach14 impact
145 instances - 95 features - 2 classes - 0 missing values
Dataset from the MLRR repository: http://axon.cs.byu.edu:5000/
153 runs0 likes8 downloads8 reach14 impact
81 instances - 12 features - 3 classes - 0 missing values