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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…
796 runs0 likes8 downloads8 reach13 impact
8192 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…
970 runs0 likes8 downloads8 reach12 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…
154 runs0 likes9 downloads9 reach13 impact
2001 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…
791 runs0 likes7 downloads7 reach13 impact
400 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…
764 runs0 likes6 downloads6 reach13 impact
400 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…
653 runs0 likes10 downloads10 reach13 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…
643 runs0 likes8 downloads8 reach13 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…
788 runs0 likes7 downloads7 reach13 impact
400 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…
779 runs0 likes7 downloads7 reach13 impact
400 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…
624 runs0 likes8 downloads8 reach13 impact
1000 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…
847 runs0 likes7 downloads7 reach13 impact
250 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…
143 runs1 likes11 downloads12 reach13 impact
531 instances - 103 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 likes9 downloads9 reach13 impact
3190 instances - 62 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…
173 runs0 likes6 downloads6 reach21 impact
106 instances - 59 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 likes5 downloads5 reach13 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…
1032 runs0 likes7 downloads7 reach13 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…
772 runs0 likes14 downloads14 reach13 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…
717 runs0 likes5 downloads5 reach12 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…
652 runs0 likes16 downloads16 reach13 impact
12960 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,…
747 runs0 likes7 downloads7 reach12 impact
145 instances - 95 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 likes19 downloads19 reach25 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…
146025 runs1 likes16 downloads17 reach24 impact
1563 instances - 38 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 reach13 impact
161 instances - 40 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 likes15 downloads15 reach24 impact
1458 instances - 38 features - 2 classes - 0 missing values
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% This is a PROMISE Software Engineering Repository data set made publicly available in order to encourage repeatable,…
109963 runs1 likes19 downloads20 reach25 impact
15545 instances - 6 features - 2 classes - 0 missing values
No data.
747 runs0 likes7 downloads7 reach13 impact
369 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 -…
15930 runs0 likes19 downloads19 reach23 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…
698 runs0 likes6 downloads6 reach12 impact
97 instances - 11 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…
104 runs0 likes4 downloads4 reach12 impact
52 instances - 10 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 likes7 downloads7 reach21 impact
340 instances - 15 features - 2 classes - 834 missing values
87 persons with lupus nephritis. Followed up 15+ years. 35 deaths. Var = duration of disease. Over 40 baseline variables avaiable from authors. Description : For description of this data set arising…
737 runs0 likes9 downloads9 reach12 impact
87 instances - 4 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 likes7 downloads7 reach13 impact
250 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…
118 runs0 likes3 downloads3 reach13 impact
195 instances - 12 features - 2 classes - 2 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…
670 runs0 likes4 downloads4 reach12 impact
62 instances - 8 features - 2 classes - 8 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…
854 runs0 likes7 downloads7 reach13 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…
707 runs0 likes6 downloads6 reach12 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…
602 runs1 likes12 downloads13 reach13 impact
13750 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…
748 runs0 likes6 downloads6 reach13 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…
753 runs0 likes10 downloads10 reach13 impact
8192 instances - 13 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 likes10 downloads10 reach13 impact
3107 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…
856 runs0 likes11 downloads11 reach13 impact
209 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…
1190 runs0 likes9 downloads9 reach12 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…
703 runs0 likes6 downloads6 reach12 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…
620 runs0 likes10 downloads10 reach13 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…
737 runs0 likes5 downloads5 reach13 impact
303 instances - 14 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…
800 runs0 likes10 downloads10 reach13 impact
209 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…
766 runs0 likes5 downloads5 reach12 impact
55 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…
812 runs0 likes7 downloads7 reach13 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…
791 runs0 likes6 downloads6 reach13 impact
250 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…
802 runs0 likes8 downloads8 reach13 impact
662 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…
806 runs0 likes8 downloads8 reach13 impact
500 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…
631 runs0 likes7 downloads7 reach13 impact
1000 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…
775 runs0 likes7 downloads7 reach12 impact
43 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…
707 runs0 likes6 downloads6 reach13 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…
686 runs0 likes5 downloads5 reach13 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…
708 runs0 likes4 downloads4 reach14 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…
683 runs0 likes5 downloads5 reach12 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…
614 runs0 likes9 downloads9 reach13 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 likes9 downloads9 reach13 impact
500 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…
773 runs0 likes14 downloads14 reach13 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…
589 runs0 likes11 downloads11 reach13 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…
625 runs0 likes10 downloads10 reach13 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…
801 runs0 likes9 downloads9 reach13 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…
808 runs1 likes9 downloads10 reach12 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…
731 runs0 likes5 downloads5 reach12 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 reach12 impact
50 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…
728 runs0 likes6 downloads6 reach12 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…
813 runs0 likes7 downloads7 reach13 impact
500 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…
819 runs0 likes10 downloads10 reach13 impact
500 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…
789 runs0 likes8 downloads8 reach12 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 reach12 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…
1164 runs0 likes7 downloads7 reach13 impact
222 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…
718 runs0 likes6 downloads6 reach13 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…
722 runs0 likes5 downloads5 reach13 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…
176 runs0 likes7 downloads7 reach12 impact
101 instances - 18 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 likes6 downloads6 reach13 impact
1340 instances - 18 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…
698 runs0 likes5 downloads5 reach12 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 reach12 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…
708 runs0 likes5 downloads5 reach13 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…
773 runs0 likes8 downloads8 reach13 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…
1133 runs0 likes15 downloads15 reach16 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…
736 runs1 likes5 downloads6 reach13 impact
452 instances - 280 features - 2 classes - 408 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…
754 runs0 likes10 downloads10 reach14 impact
8844 instances - 57 features - 2 classes - 34843 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 likes6 downloads6 reach13 impact
194 instances - 30 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…
723 runs0 likes6 downloads6 reach13 impact
366 instances - 35 features - 2 classes - 8 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 likes9 downloads9 reach13 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…
746 runs0 likes7 downloads7 reach12 impact
72 instances - 4 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 reach13 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…
1149 runs0 likes10 downloads10 reach12 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…
676 runs0 likes13 downloads13 reach13 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…
815 runs0 likes8 downloads8 reach13 impact
336 instances - 8 features - 2 classes - 0 missing values
Publication Request: >>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> This file describes the contents of the heart-disease directory. This directory contains 4 databases…
1763 runs0 likes10 downloads10 reach7 impact
303 instances - 14 features - 2 classes - 7 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 reach7 impact
208 instances - 61 features - 2 classes - 0 missing values
Donor: Will Taylor (taylor@pluto.arc.nasa.gov) In this version (version 2), some features were removed. It is unclear why of how this was done.
1883 runs1 likes10 downloads11 reach7 impact
368 instances - 23 features - 2 classes - 1927 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 runs4 likes88 downloads92 reach9 impact
4601 instances - 58 features - 2 classes - 0 missing values
1. Title: INDUCE Trains Data set 2. Sources: - Donor: GMU, Center for AI, Software Librarian, Eric E. Bloedorn (bloedorn@aic.gmu.edu) - Original owners: Ryszard S. Michalski (michalski@aic.gmu.edu)…
1973 runs0 likes9 downloads9 reach12 impact
10 instances - 33 features - 2 classes - 51 missing values
1. Title: Haberman's Survival Data 2. Sources: (a) Donor: Tjen-Sien Lim (limt@stat.wisc.edu) (b) Date: March 4, 1999 3. Past Usage: 1. Haberman, S. J. (1976). Generalized Residuals for Log-Linear…
3241 runs1 likes19 downloads20 reach7 impact
306 instances - 4 features - 2 classes - 0 missing values
This database encodes the complete set of possible board configurations at the end of tic-tac-toe games, where "x" is assumed to have played first. The target concept is "win for x" (i.e., true when…
386329 runs2 likes75 downloads77 reach8 impact
958 instances - 10 features - 2 classes - 0 missing values
Data file: This data from "Problem-Solving" on "backache in pregnancy" is in somewhat different format from that listed in the book. Each integer is preceded by a space. This makes it easier to read.…
174 runs0 likes6 downloads6 reach13 impact
180 instances - 33 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 likes10 downloads10 reach12 impact
100 instances - 7 features - 2 classes - 0 missing values