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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.…
64659 runs1 likes29 downloads30 reach25 impact
19020 instances - 12 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
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 likes22 downloads22 reach16 impact
98528 instances - 101 features - 2 classes - 0 missing values
Fast training of support vector machines using sequential minimal optimization. In Bernhard Scholkopf, Christopher J. C. Burges, and Alexander J. Smola, editors, Advances in Kernel Methods - Support…
564 runs0 likes11 downloads11 reach23 impact
36974 instances - 124 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
624 runs0 likes10 downloads10 reach15 impact
15000 instances - 49 features - 2 classes - 0 missing values
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 reach15 impact
468 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…
604 runs0 likes9 downloads9 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…
739 runs0 likes11 downloads11 reach15 impact
4052 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…
760 runs0 likes13 downloads13 reach15 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…
567 runs0 likes14 downloads14 reach15 impact
40768 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…
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…
854 runs0 likes7 downloads7 reach15 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…
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…
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…
107 runs0 likes4 downloads4 reach15 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…
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…
760 runs0 likes11 downloads11 reach15 impact
8192 instances - 22 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…
768 runs0 likes7 downloads7 reach15 impact
450 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…
751 runs0 likes7 downloads7 reach15 impact
475 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…
781 runs0 likes8 downloads8 reach15 impact
500 instances - 51 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
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…
773 runs0 likes8 downloads8 reach15 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…
720 runs0 likes8 downloads8 reach15 impact
506 instances - 21 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…
581 runs0 likes11 downloads11 reach15 impact
20640 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…
773 runs0 likes6 downloads6 reach15 impact
500 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…
739 runs0 likes6 downloads6 reach15 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…
782 runs0 likes6 downloads6 reach15 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…
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). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
726 runs0 likes10 downloads10 reach15 impact
576 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…
554 runs0 likes10 downloads10 reach15 impact
40768 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…
786 runs0 likes6 downloads6 reach15 impact
250 instances - 51 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
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…
818 runs0 likes7 downloads7 reach15 impact
284 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…
816 runs0 likes7 downloads7 reach15 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 reach15 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…
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…
786 runs0 likes7 downloads7 reach15 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…
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…
812 runs0 likes7 downloads7 reach15 impact
559 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…
774 runs0 likes9 downloads9 reach15 impact
559 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…
769 runs0 likes7 downloads7 reach15 impact
559 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…
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…
814 runs0 likes7 downloads7 reach15 impact
500 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…
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…
104 runs0 likes6 downloads6 reach15 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…
140 runs0 likes6 downloads6 reach15 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…
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…
723 runs0 likes6 downloads6 reach15 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…
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…
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…
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…
815 runs0 likes9 downloads9 reach15 impact
336 instances - 8 features - 2 classes - 0 missing values
PRO FOOTBALL SCORES How well do the oddsmakers of Las Vegas predict the outcome of professional football games? Is there really a home field advantage - if so how large is it? Are teams that play the…
15930 runs0 likes19 downloads19 reach25 impact
672 instances - 10 features - 2 classes - 1200 missing values
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. Each line…
174 runs0 likes6 downloads6 reach15 impact
180 instances - 32 features - 2 classes - 0 missing values
Schizophrenic Eye-Tracking Data in Rubin and Wu (1997) Biometrics.\ Information about the dataset CLASSTYPE: nominal CLASSINDEX: last
748 runs0 likes7 downloads7 reach24 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. 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
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 reach15 impact
250 instances - 3 features - 2 classes - 0 missing values
Compilation of promoters with known transcriptional start points for E. coli genes. The task is to recognize promoters in strings that represent nucleotides (one of A, G, T, or C). A promoter is a…
138 runs1 likes9 downloads10 reach12 impact
106 instances - 58 features - 2 classes - 0 missing values
The dataset (originally named ELEC2) contains 45,312 instances dated from 7 May 1996 to 5 December 1998. Each example of the dataset refers to a period of 30 minutes, i.e. there are 48 instances for…
106854 runs3 likes40 downloads43 reach12 impact
45312 instances - 9 features - 2 classes - 0 missing values
No data.
867 runs0 likes12 downloads12 reach9 impact
39366 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…
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…
739 runs0 likes7 downloads7 reach15 impact
475 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…
755 runs0 likes6 downloads6 reach15 impact
250 instances - 51 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
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…
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…
746 runs0 likes6 downloads6 reach15 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…
780 runs0 likes10 downloads10 reach15 impact
625 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…
792 runs0 likes7 downloads7 reach15 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…
775 runs0 likes13 downloads13 reach15 impact
2178 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…
756 runs0 likes6 downloads6 reach15 impact
310 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…
604 runs0 likes14 downloads14 reach15 impact
22784 instances - 17 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 likes8 downloads8 reach15 impact
235 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…
774 runs0 likes14 downloads14 reach15 impact
9517 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 likes5 downloads5 reach14 impact
52 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…
761 runs0 likes14 downloads14 reach15 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…
752 runs0 likes5 downloads5 reach14 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…
598 runs0 likes8 downloads8 reach15 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…
903 runs0 likes8 downloads8 reach15 impact
468 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…
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). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
636 runs0 likes8 downloads8 reach15 impact
1000 instances - 51 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
773 runs0 likes6 downloads6 reach15 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…
963 runs0 likes11 downloads11 reach15 impact
380 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…
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). 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 reach15 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…
135 runs0 likes9 downloads9 reach15 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…
173 runs0 likes6 downloads6 reach24 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 likes5 downloads5 reach15 impact
412 instances - 9 features - 2 classes - 96 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 likes8 downloads8 reach15 impact
559 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…
1032 runs0 likes7 downloads7 reach15 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 likes15 downloads15 reach15 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…
652 runs0 likes17 downloads17 reach15 impact
12960 instances - 9 features - 2 classes - 0 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