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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…
806 runs0 likes8 downloads8 reach15 impact
186 instances - 61 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 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…
970 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…
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…
806 runs0 likes8 downloads8 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…
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…
817 runs0 likes8 downloads8 reach15 impact
400 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…
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…
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…
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). The multi-class target feature is converted to a two-class nominal target feature by re-labeling the majority class as positive ('P') and…
757 runs0 likes8 downloads8 reach15 impact
400 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…
621 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…
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…
643 runs0 likes8 downloads8 reach15 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…
624 runs0 likes8 downloads8 reach15 impact
1000 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…
744 runs0 likes8 downloads8 reach16 impact
7019 instances - 61 features - 2 classes - 43814 missing values
Binarized version of the original data set (see version 1). The multi-class target feature is converted to a two-class nominal target feature by re-labeling the majority class as positive ('P') and…
712 runs0 likes8 downloads8 reach15 impact
898 instances - 39 features - 2 classes - 22175 missing values
Binarized version of the original data set (see version 1). The multi-class target feature is converted to a two-class nominal target feature by re-labeling the majority class as positive ('P') and…
792 runs0 likes8 downloads8 reach15 impact
2000 instances - 48 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). The multi-class target feature is converted to a two-class nominal target feature by re-labeling the majority class as positive ('P') and…
810 runs0 likes8 downloads8 reach15 impact
846 instances - 19 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…
1059 runs0 likes8 downloads8 reach15 impact
264 instances - 3 features - 2 classes - 0 missing values
--Title: AR1 /Software Defect Prediction --Date: February, 4th, 2009 --Data from a Turkish white-goods manufacturer --Donated by: Software Research Laboratory (Softlab), Bogazici University, Istanbul,…
756 runs0 likes8 downloads8 reach14 impact
121 instances - 30 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…
789 runs0 likes8 downloads8 reach14 impact
73 instances - 6 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
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…
763 runs0 likes8 downloads8 reach15 impact
250 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…
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…
169 runs0 likes8 downloads8 reach16 impact
600 instances - 61 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). The multi-class target feature is converted to a two-class nominal target feature by re-labeling the majority class as positive ('P') and…
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…
777 runs0 likes8 downloads8 reach15 impact
625 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…
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…
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). The multi-class target feature is converted to a two-class nominal target feature by re-labeling the majority class as positive ('P') and…
801 runs0 likes8 downloads8 reach15 impact
841 instances - 71 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). The multi-class target feature is converted to a two-class nominal target feature by re-labeling the majority class as positive ('P') and…
748 runs0 likes8 downloads8 reach14 impact
148 instances - 19 features - 2 classes - 0 missing values
* Dataset Title: AutoUniv Dataset data problem: autoUniv-au6-250-drift-au6-cd1-500 * Abstract: AutoUniv is an advanced data generator for classifications tasks. The aim is to reflect the nuances and…
11011 runs0 likes9 downloads9 reach47 impact
750 instances - 41 features - 8 classes - 0 missing values
cast metal 1
111 runs0 likes9 downloads9 reach13 impact
327 instances - 38 features - 2 classes - 0 missing values
No data.
253 runs0 likes9 downloads9 reach9 impact
1076790 instances - 30 features - 2 classes - 7275 missing values
The experiments were carried out with a group of 30 volunteers within an age bracket of 19-48 years. They performed a protocol of activities composed of six basic activities: three static postures…
83 runs0 likes9 downloads9 reach12 impact
180 instances - 68 features - 6 classes - 0 missing values
This is a dataset obtained from the StatLib repository. Here is the included description: The data provided are daily stock prices from January 1988 through October 1991, for ten aerospace companies.…
5 runs1 likes9 downloads10 reach9 impact
950 instances - 10 features - 0 classes - 0 missing values
This simple domain contains 7 Boolean attributes and 10 classes, the set of decimal digits. Recall that LED displays contain 7 light-emitting diodes -- hence the reason for 7 attributes. The class…
13006 runs0 likes9 downloads9 reach18 impact
500 instances - 8 features - 10 classes - 0 missing values
General Description of Thyroid Disease Databases and Related Files This directory contains 6 databases, corresponding test set, and corresponding documentation. They were left at the University of…
31 runs1 likes9 downloads10 reach13 impact
2800 instances - 27 features - 5 classes - 0 missing values
1: Abstract: This is a 20 dimensional, 2 class classification problem. Each class is drawn from a multivariate normal distribution. Class 1 has mean zero and covariance 4 times the identity. Class 2…
120 runs0 likes9 downloads9 reach14 impact
7400 instances - 21 features - 2 classes - 0 missing values
* Donor: David W. Aha (aha '@' ics.uci.edu) (714) 856-8779 * Data Set Information: This database contains 76 attributes, but all published experiments refer to using a subset of 14 of them. In…
170 runs0 likes9 downloads9 reach13 impact
123 instances - 13 features - 5 classes - 0 missing values
Data on predicting clicks on ads in a search engine.
0 runs0 likes9 downloads9 reach13 impact
1496391 instances - 10 features - 2 classes - 0 missing values
A dataset relating characteristics of telephony account features and usage and whether or not the customer churned. Originally used in [Discovering Knowledge in Data: An Introduction to Data…
7482 runs2 likes9 downloads11 reach24 impact
5000 instances - 21 features - 2 classes - 0 missing values
### Attribute Information * The first column is the class label (1 for signal, 0 for background) * 21 low-level features (kinematic properties): lepton pT, lepton eta, lepton phi, missing energy…
14236 runs1 likes9 downloads10 reach28 impact
98050 instances - 29 features - 2 classes - 9 missing values
* Dataset Title: AutoUniv Dataset data problem: autoUniv-au1-1000 * Abstract: AutoUniv is an advanced data generator for classifications tasks. The aim is to reflect the nuances and heterogeneity of…
3255 runs1 likes9 downloads10 reach23 impact
1000 instances - 21 features - 2 classes - 0 missing values
No data.
268 runs0 likes9 downloads9 reach47 impact
3075 instances - 12433 features - 6 classes - 0 missing values
No data.
373 runs0 likes9 downloads9 reach62 impact
918 instances - 3013 features - 10 classes - 0 missing values
Modified by TunedIT (converted to ARFF format) GINA is digit recognition database The task of GINA is handwritten digit recognition. For the "prior knowledge track" we chose the problem of separating…
548 runs0 likes9 downloads9 reach16 impact
3468 instances - 785 features - 2 classes - 0 missing values
### UNIX User Data This file contains 9 sets of sanitized user data drawn from the command histories of 8 UNIX computer users at Purdue over the course of up to 2 years (USER0 and USER1 were generated…
11 runs0 likes9 downloads9 reach14 impact
9100 instances - 3 features - 9 classes - 0 missing values
This is the famous covertype dataset in its binary version, retrieved 2013-11-13 from the libSVM site (called covtype.binary there). Additional to the preprocessing done there (see LibSVM site for…
22 runs0 likes9 downloads9 reach15 impact
581012 instances - 55 features - 2 classes - 0 missing values
Data originating from the book "Analyzing Categorical Data" by Jeffrey S. Simonoff. ### Attribute Information: 1. Sex - Male/Female 2. Age - numerical integer range 3. Race - categorical 4. AIDS -…
1087 runs0 likes9 downloads9 reach15 impact
50 instances - 5 features - 2 classes - 0 missing values
Donor: Will Taylor (taylor@pluto.arc.nasa.gov) Database of surgeries on horses. Possible class attributes: 24 (whether lesion is surgical), others include: 23, 25, 26, and 27 Notes: * Hospital_Number…
236 runs0 likes9 downloads9 reach9 impact
368 instances - 27 features - 2 classes - 1927 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
Space Shuttle Autolanding Domain - Donor: B. Cestnik Jozef Stefan Institute - Past Usage: (several, it appears) Example: Michie,D. (1988). The Fifth Generation's Unbridged Gap. In Rolf Herken (Ed.)…
1466 runs0 likes9 downloads9 reach9 impact
15 instances - 7 features - 2 classes - 26 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 reach15 impact
10 instances - 33 features - 2 classes - 51 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
The 1982 annual meetings of the American Statistical Association (ASA) will be held August 16-19, 1982 in Cincinnati. At that meeting, the ASA Committee on Statistical Graphics plans to sponsor an…
759 runs0 likes9 downloads9 reach24 impact
209 instances - 9 features - 2 classes - 15 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…
615 runs0 likes9 downloads9 reach15 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…
1058 runs0 likes9 downloads9 reach15 impact
167 instances - 5 features - 2 classes - 0 missing values
No data.
965 runs0 likes9 downloads9 reach9 impact
55296 instances - 10 features - 3 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…
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…
608 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…
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…
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…
575 runs0 likes9 downloads9 reach15 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…
1111 runs0 likes9 downloads9 reach14 impact
100 instances - 6 features - 2 classes - 0 missing values
No data.
414 runs0 likes9 downloads9 reach62 impact
690 instances - 8262 features - 10 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 likes9 downloads9 reach14 impact
45 instances - 47 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…
796 runs0 likes9 downloads9 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…
988 runs0 likes9 downloads9 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…
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…
646 runs0 likes9 downloads9 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…
638 runs0 likes9 downloads9 reach15 impact
1000 instances - 26 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). The multi-class target feature is converted to a two-class nominal target feature by re-labeling the majority class as positive ('P') and…
778 runs0 likes9 downloads9 reach15 impact
5000 instances - 41 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). The multi-class target feature is converted to a two-class nominal target feature by re-labeling the majority class as positive ('P') and…
794 runs0 likes9 downloads9 reach15 impact
2000 instances - 65 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). 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 likes9 downloads9 reach15 impact
315 instances - 14 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 reach15 impact
2001 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…
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…
614 runs0 likes9 downloads9 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…
771 runs0 likes9 downloads9 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…
709 runs0 likes9 downloads9 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…
767 runs0 likes9 downloads9 reach15 impact
189 instances - 10 features - 2 classes - 0 missing values
1. Title/Topic: The transition of the DATATRIEVE product from version 6.0 to version 6.1 2. Sources: -- Creators: DATATRIEVETM project carried out at Digital Engineering Italy -- Donor: Guenther Ruhe…
908 runs0 likes9 downloads9 reach14 impact
130 instances - 9 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…
754 runs0 likes9 downloads9 reach14 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…
801 runs0 likes9 downloads9 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…
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). 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). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
608 runs1 likes9 downloads10 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…
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…
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). The multi-class target feature is converted to a two-class nominal target feature by re-labeling the majority class as positive ('P') and…
733 runs0 likes9 downloads9 reach16 impact
7485 instances - 56 features - 2 classes - 32427 missing values
Binarized version of the original data set (see version 1). The multi-class target feature is converted to a two-class nominal target feature by re-labeling the majority class as positive ('P') and…
737 runs0 likes9 downloads9 reach15 impact
3772 instances - 30 features - 2 classes - 6064 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…
842 runs0 likes9 downloads9 reach15 impact
323 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…
745 runs0 likes9 downloads9 reach15 impact
240 instances - 125 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…
780 runs0 likes9 downloads9 reach15 impact
178 instances - 14 features - 2 classes - 0 missing values
One of the NASA Metrics Data Program defect data sets. Data from software for science data processing. Data comes from McCabe and Halstead features extractors of source code. These features were…
777 runs0 likes9 downloads9 reach15 impact
458 instances - 40 features - 2 classes - 0 missing values