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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…
121 runs0 likes6 downloads6 reach6 impact
46 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…
113 runs0 likes4 downloads4 reach6 impact
40 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…
810 runs0 likes6 downloads6 reach6 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…
744 runs0 likes7 downloads7 reach6 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…
103 runs0 likes5 downloads5 reach6 impact
107 instances - 13 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 reach6 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…
1147 runs0 likes10 downloads10 reach6 impact
138 instances - 3 features - 2 classes - 0 missing values
The AAUP dataset for the ASA Statistical Graphics Section's 1995 Data Analysis Exposition contains information on faculty salaries for 1161 American colleges and universities. The data may be obtained…
32 runs0 likes3 downloads3 reach6 impact
1161 instances - 17 features - 4 classes - 256 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 reach6 impact
67 instances - 17 features - 5 classes - 0 missing values
analcatdata A collection of data sets used in the book "Analyzing Categorical Data," by Jeffrey S. Simonoff, Springer-Verlag, New York, 2003. The submission consists of a zip file containing two…
103 runs0 likes4 downloads4 reach6 impact
92 instances - 11 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…
587 runs0 likes5 downloads5 reach6 impact
61 instances - 19 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. Description : For description of this data set arising…
735 runs0 likes7 downloads7 reach6 impact
87 instances - 4 features - 2 classes - 0 missing values
analcatdata A collection of data sets used in the book "Analyzing Categorical Data," by Jeffrey S. Simonoff, Springer-Verlag, New York, 2003. The submission consists of a zip file containing two…
581 runs0 likes5 downloads5 reach6 impact
400 instances - 6 features - 4 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…
117 runs0 likes5 downloads5 reach6 impact
50 instances - 7 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…
102 runs0 likes4 downloads4 reach6 impact
52 instances - 10 features - 2 classes - 0 missing values
CODING: 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 =…
560 runs0 likes4 downloads4 reach6 impact
72 instances - 4 features - 6 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 reach6 impact
87 instances - 11 features - 2 classes - 0 missing values
SUMMARY: Data from an experiment on the affects of machine adjustments on the time to count bolts. Data appear as the STATS (Issue 10) Challenge. DATA: Submitted by W. Robert Stephenson, Iowa State…
752 runs0 likes8 downloads8 reach6 impact
40 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…
683 runs0 likes5 downloads5 reach6 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…
752 runs0 likes6 downloads6 reach6 impact
38 instances - 6 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
764 runs0 likes6 downloads6 reach6 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…
102 runs0 likes4 downloads4 reach6 impact
67 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…
107 runs0 likes4 downloads4 reach6 impact
66 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…
100 runs0 likes3 downloads3 reach6 impact
31 instances - 17 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…
1136 runs0 likes8 downloads8 reach6 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…
984 runs0 likes8 downloads8 reach6 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…
706 runs0 likes5 downloads5 reach6 impact
62 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…
757 runs0 likes6 downloads6 reach6 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…
1200 runs0 likes9 downloads9 reach6 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…
570 runs0 likes6 downloads6 reach6 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…
730 runs0 likes5 downloads5 reach6 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…
733 runs0 likes3 downloads3 reach6 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…
106 runs0 likes3 downloads3 reach6 impact
74 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…
1250 runs0 likes9 downloads9 reach6 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…
792 runs0 likes7 downloads7 reach6 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…
721 runs0 likes5 downloads5 reach6 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…
788 runs0 likes7 downloads7 reach6 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…
176 runs0 likes6 downloads6 reach6 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…
688 runs0 likes4 downloads4 reach6 impact
294 instances - 14 features - 2 classes - 782 missing values
Binarized version of the original data set (see version 1). The multi-class target feature is converted to a two-class nominal target feature by re-labeling the majority class as positive ('P') and…
698 runs0 likes5 downloads5 reach6 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…
717 runs0 likes5 downloads5 reach6 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…
453 runs0 likes5 downloads5 reach6 impact
108 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…
789 runs0 likes7 downloads7 reach6 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…
735 runs0 likes5 downloads5 reach6 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…
770 runs0 likes8 downloads8 reach6 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…
1024 runs0 likes8 downloads8 reach6 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…
1071 runs0 likes10 downloads10 reach6 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…
738 runs0 likes5 downloads5 reach6 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…
1821 runs0 likes9 downloads9 reach6 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…
755 runs0 likes4 downloads4 reach6 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…
778 runs0 likes7 downloads7 reach6 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…
726 runs0 likes6 downloads6 reach6 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…
808 runs1 likes9 downloads10 reach6 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…
729 runs0 likes5 downloads5 reach6 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…
118 runs0 likes5 downloads5 reach6 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…
787 runs0 likes7 downloads7 reach6 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…
754 runs0 likes10 downloads10 reach6 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 reach6 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…
1266 runs0 likes11 downloads11 reach6 impact
131 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…
141 runs0 likes7 downloads7 reach6 impact
500 instances - 24 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 reach6 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…
687 runs0 likes5 downloads5 reach6 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…
1137 runs0 likes7 downloads7 reach6 impact
132 instances - 5 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 likes12 downloads12 reach6 impact
72 instances - 7130 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 likes7 downloads7 reach6 impact
145 instances - 95 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 likes8 downloads8 reach6 impact
101 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,…
908 runs0 likes9 downloads9 reach6 impact
130 instances - 9 features - 2 classes - 0 missing values
No data.
794 runs1 likes13 downloads14 reach6 impact
107 instances - 30 features - 2 classes - 0 missing values
No data.
726 runs0 likes9 downloads9 reach6 impact
36 instances - 30 features - 2 classes - 0 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 reach6 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 reach6 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 reach6 impact
7485 instances - 61 features - 7 classes - 52048 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…
50 runs0 likes5 downloads5 reach6 impact
95 instances - 10 features - 5 classes - 9 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…
1028 runs0 likes8 downloads8 reach6 impact
132 instances - 4 features - 2 classes - 0 missing values
Yeast dataset Past Usage: André Elisseeff and Jason Weston. A kernel method for multi-labelled classification. In Thomas G. Dietterich, Susan Becker, and Zoubin Ghahramani, editors, Advances in…
139 runs0 likes8 downloads8 reach6 impact
2417 instances - 117 features - 2 classes - 0 missing values
Short Summary: Lists estimates of the percentage of body fat determined by underwater weighing and various body circumference measurements for 252 men. Classroom use of this data set: This data set…
0 runs0 likes4 downloads4 reach7 impact
252 instances - 15 features - 0 classes - 0 missing values
!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! Attributes 2 and 8 deleted. As used by Kilpatrick, D. & Cameron-Jones, M. (1998). Numeric prediction using instance-based…
2 runs0 likes2 downloads2 reach7 impact
209 instances - 8 features - 0 classes - 0 missing values
1. Title: meta-data 2. Sources: (a) Creator: LIACC - University of Porto R.Campo Alegre 823 4150 PORTO (b) Donor: P.B.Brazdil or J.Gama Tel.: +351 600 1672 LIACC, University of Porto Fax.: +351 600…
32 runs0 likes2 downloads2 reach7 impact
528 instances - 22 features - 0 classes - 504 missing values
!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! Attributes 2,4, and 6 deleted. Midrange price treated as the class attribute. As used by Kilpatrick, D. & Cameron-Jones, M.…
0 runs0 likes0 downloads0 reach7 impact
93 instances - 23 features - 0 classes - 14 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 likes2 downloads2 reach7 impact
363 instances - 10937 features - 2 classes - 0 missing values
GEMLeR provides a collection of gene expression datasets that can be used for benchmarking gene expression oriented machine learning algorithms. They can be used for estimation of different quality…
77 runs0 likes2 downloads2 reach7 impact
329 instances - 10937 features - 2 classes - 0 missing values
GEMLeR provides a collection of gene expression datasets that can be used for benchmarking gene expression oriented machine learning algorithms. They can be used for estimation of different quality…
77 runs0 likes3 downloads3 reach7 impact
337 instances - 10937 features - 2 classes - 0 missing values
GEMLeR provides a collection of gene expression datasets that can be used for benchmarking gene expression oriented machine learning algorithms. They can be used for estimation of different quality…
65 runs0 likes3 downloads3 reach7 impact
468 instances - 10937 features - 2 classes - 0 missing values
GEMLeR provides a collection of gene expression datasets that can be used for benchmarking gene expression oriented machine learning algorithms. They can be used for estimation of different quality…
67 runs0 likes1 downloads1 reach7 impact
458 instances - 10937 features - 2 classes - 0 missing values
GEMLeR provides a collection of gene expression datasets that can be used for benchmarking gene expression oriented machine learning algorithms. They can be used for estimation of different quality…
65 runs0 likes3 downloads3 reach7 impact
470 instances - 10937 features - 2 classes - 0 missing values
GEMLeR provides a collection of gene expression datasets that can be used for benchmarking gene expression oriented machine learning algorithms. They can be used for estimation of different quality…
77 runs0 likes3 downloads3 reach7 impact
193 instances - 10937 features - 2 classes - 0 missing values
GEMLeR provides a collection of gene expression datasets that can be used for benchmarking gene expression oriented machine learning algorithms. They can be used for estimation of different quality…
77 runs0 likes2 downloads2 reach7 impact
203 instances - 10937 features - 2 classes - 0 missing values
GEMLeR provides a collection of gene expression datasets that can be used for benchmarking gene expression oriented machine learning algorithms. They can be used for estimation of different quality…
65 runs0 likes2 downloads2 reach7 impact
347 instances - 10937 features - 2 classes - 0 missing values
GEMLeR provides a collection of gene expression datasets that can be used for benchmarking gene expression oriented machine learning algorithms. They can be used for estimation of different quality…
77 runs0 likes3 downloads3 reach7 impact
355 instances - 10937 features - 2 classes - 0 missing values
GEMLeR provides a collection of gene expression datasets that can be used for benchmarking gene expression oriented machine learning algorithms. They can be used for estimation of different quality…
77 runs0 likes4 downloads4 reach7 impact
250 instances - 10937 features - 2 classes - 0 missing values
GEMLeR provides a collection of gene expression datasets that can be used for benchmarking gene expression oriented machine learning algorithms. They can be used for estimation of different quality…
65 runs0 likes2 downloads2 reach7 impact
324 instances - 10937 features - 2 classes - 0 missing values
GEMLeR provides a collection of gene expression datasets that can be used for benchmarking gene expression oriented machine learning algorithms. They can be used for estimation of different quality…
77 runs0 likes2 downloads2 reach7 impact
413 instances - 10937 features - 2 classes - 0 missing values
GEMLeR provides a collection of gene expression datasets that can be used for benchmarking gene expression oriented machine learning algorithms. They can be used for estimation of different quality…
80 runs0 likes5 downloads5 reach7 impact
405 instances - 10937 features - 2 classes - 0 missing values
GEMLeR provides a collection of gene expression datasets that can be used for benchmarking gene expression oriented machine learning algorithms. They can be used for estimation of different quality…
77 runs0 likes2 downloads2 reach7 impact
201 instances - 10937 features - 2 classes - 0 missing values
GEMLeR provides a collection of gene expression datasets that can be used for benchmarking gene expression oriented machine learning algorithms. They can be used for estimation of different quality…
65 runs0 likes2 downloads2 reach7 impact
412 instances - 10937 features - 2 classes - 0 missing values
GEMLeR provides a collection of gene expression datasets that can be used for benchmarking gene expression oriented machine learning algorithms. They can be used for estimation of different quality…
78 runs0 likes3 downloads3 reach7 impact
421 instances - 10937 features - 2 classes - 0 missing values
GEMLeR provides a collection of gene expression datasets that can be used for benchmarking gene expression oriented machine learning algorithms. They can be used for estimation of different quality…
77 runs0 likes2 downloads2 reach7 impact
384 instances - 10937 features - 2 classes - 0 missing values
No data.
0 runs0 likes3 downloads3 reach7 impact
697641 instances - 47237 features - 0 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…
0 runs0 likes1 downloads1 reach7 impact
323 instances - 5 features - 0 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 likes2 downloads2 reach7 impact
322 instances - 10937 features - 2 classes - 0 missing values