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* 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 runs0 likes8 downloads8 reach16 impact
1000 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…
762 runs0 likes9 downloads9 reach8 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…
617 runs0 likes11 downloads11 reach8 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…
772 runs0 likes7 downloads7 reach8 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…
773 runs0 likes11 downloads11 reach8 impact
8641 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…
802 runs0 likes8 downloads8 reach8 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…
800 runs0 likes9 downloads9 reach8 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…
646 runs0 likes9 downloads9 reach8 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…
788 runs0 likes7 downloads7 reach8 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…
817 runs0 likes8 downloads8 reach8 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…
638 runs0 likes9 downloads9 reach8 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…
764 runs0 likes6 downloads6 reach8 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 reach8 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 reach8 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…
653 runs0 likes10 downloads10 reach8 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 reach8 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…
847 runs0 likes7 downloads7 reach8 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…
817 runs0 likes7 downloads7 reach8 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…
791 runs0 likes7 downloads7 reach8 impact
400 instances - 8 features - 2 classes - 0 missing values
* Abstract: Oxford Parkinson's Disease Detection Dataset * Source: The dataset was created by Max Little of the University of Oxford, in collaboration with the National Centre for Voice and Speech,…
179 runs1 likes14 downloads15 reach7 impact
195 instances - 23 features - 2 classes - 0 missing values
* Twonorm dataset This is an implementation of Leo Breiman's twonorm example[1]. It is a 20 dimensional, 2 class classification example. Each class is drawn from a multivariate normal distribution…
118 runs0 likes5 downloads5 reach7 impact
7400 instances - 21 features - 2 classes - 0 missing values
* Title: Planning Relax Data Set * Abstract: The dataset concerns with the classification of two mental stages from recorded EEG signals: Planning (during imagination of motor act) and Relax state. *…
141 runs0 likes8 downloads8 reach7 impact
182 instances - 13 features - 2 classes - 0 missing values
The aim of this dataset is to distinguish between nasal (class 0) and oral sounds (class 1). Five different attributes were chosen to characterize each vowel: they are the amplitudes of the five first…
216320 runs5 likes33 downloads38 reach21 impact
5404 instances - 6 features - 2 classes - 0 missing values
Current dataset was adapted to ARFF format from the UCI version. Sample code ID's were removed. ! Note that there is also a related Breast Cancer Wisconsin (Original) Data Set with a different set of…
225108 runs3 likes34 downloads37 reach20 impact
569 instances - 31 features - 2 classes - 0 missing values
* Dataset Title: Vertebra Column - 2 classes * Abstract: Data set containing values for six biomechanical features used to classify orthopaedic patients into 3 classes (normal, disk hernia or…
124 runs0 likes5 downloads5 reach7 impact
310 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…
739 runs0 likes6 downloads6 reach8 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…
734 runs0 likes7 downloads7 reach7 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…
808 runs1 likes9 downloads10 reach7 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…
1078 runs0 likes11 downloads11 reach7 impact
108 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…
819 runs0 likes10 downloads10 reach8 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…
801 runs0 likes9 downloads9 reach8 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…
775 runs0 likes6 downloads6 reach8 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…
788 runs0 likes7 downloads7 reach7 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…
786 runs0 likes6 downloads6 reach8 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…
816 runs0 likes7 downloads7 reach8 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…
779 runs0 likes7 downloads7 reach8 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…
802 runs0 likes14 downloads14 reach8 impact
3848 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…
786 runs0 likes7 downloads7 reach8 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…
1268 runs0 likes11 downloads11 reach7 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…
818 runs0 likes7 downloads7 reach8 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…
813 runs0 likes7 downloads7 reach8 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…
785 runs0 likes7 downloads7 reach8 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…
748 runs0 likes6 downloads6 reach8 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…
572 runs0 likes6 downloads6 reach7 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…
763 runs0 likes8 downloads8 reach8 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…
614 runs0 likes9 downloads9 reach8 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…
806 runs0 likes6 downloads6 reach8 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…
760 runs0 likes13 downloads13 reach8 impact
1156 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…
767 runs0 likes9 downloads9 reach8 impact
189 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…
814 runs0 likes7 downloads7 reach8 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…
774 runs0 likes9 downloads9 reach8 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…
812 runs0 likes7 downloads7 reach8 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…
813 runs0 likes7 downloads7 reach8 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…
810 runs0 likes6 downloads6 reach7 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…
797 runs0 likes7 downloads7 reach8 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…
807 runs0 likes7 downloads7 reach8 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…
842 runs0 likes9 downloads9 reach8 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…
775 runs0 likes6 downloads6 reach8 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…
769 runs0 likes7 downloads7 reach8 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…
791 runs0 likes6 downloads6 reach8 impact
250 instances - 11 features - 2 classes - 0 missing values
Forecasting skewed biased stochastic ozone days: analyses, solutions and beyond, Knowledge and Information Systems, Vol. 14, No. 3, 2008. 1 . Abstract: Two ground ozone level data sets are included in…
184415 runs0 likes15 downloads15 reach20 impact
2534 instances - 73 features - 2 classes - 0 missing values
All data is from one continuous EEG measurement with the Emotiv EEG Neuroheadset. The duration of the measurement was 117 seconds. The eye state was detected via a camera during the EEG measurement…
165222 runs3 likes92 downloads95 reach21 impact
14980 instances - 15 features - 2 classes - 0 missing values
Source: David Gil, dgil '@' dtic.ua.es, Lucentia Research Group, Department of Computer Technology, University of Alicante Jose Luis Girela, girela '@' ua.es, Department of Biotechnology, University…
451 runs0 likes7 downloads7 reach6 impact
100 instances - 10 features - 2 classes - 0 missing values
An artificial data set where instances belongs to several clusters with a banana shape. There are two attributes At1 and At2 corresponding to the x and y axis, respectively. The class label (-1 and 1)…
163 runs2 likes16 downloads18 reach7 impact
5300 instances - 3 features - 2 classes - 0 missing values
Lucas, D. D., Klein, R., Tannahill, J., Ivanova, D., Brandon, S., Domyancic, D., and Zhang, Y.: Failure analysis of parameter-induced simulation crashes in climate models, Geosci. Model Dev. Discuss.,…
162436 runs0 likes21 downloads21 reach18 impact
540 instances - 21 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…
639 runs0 likes12 downloads12 reach8 impact
20000 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…
766 runs0 likes11 downloads11 reach8 impact
2000 instances - 217 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 runs0 likes7 downloads7 reach8 impact
1473 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…
141 runs0 likes7 downloads7 reach7 impact
500 instances - 24 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 reach8 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…
734 runs0 likes10 downloads10 reach8 impact
506 instances - 14 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…
773 runs0 likes8 downloads8 reach8 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…
176 runs0 likes7 downloads7 reach7 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…
801 runs0 likes8 downloads8 reach8 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…
758 runs0 likes10 downloads10 reach8 impact
2000 instances - 77 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 likes7 downloads7 reach8 impact
846 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…
792 runs0 likes8 downloads8 reach8 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…
778 runs0 likes9 downloads9 reach8 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…
765 runs0 likes12 downloads12 reach8 impact
5620 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…
780 runs0 likes8 downloads8 reach8 impact
178 instances - 14 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…
857 runs0 likes12 downloads12 reach10 impact
9961 instances - 15 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 reach11 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…
777 runs0 likes8 downloads8 reach8 impact
625 instances - 5 features - 2 classes - 0 missing values
No data.
253 runs0 likes9 downloads9 reach2 impact
1076790 instances - 30 features - 2 classes - 7275 missing values
This dataset classifies people described by a set of attributes as good or bad credit risks. This dataset comes with a cost matrix: ``` Good Bad (predicted) Good 0 1 (actual) Bad 5 0 ``` It is worse…
505566 runs17 likes204 downloads221 reach12 impact
1000 instances - 21 features - 2 classes - 0 missing values
The datasets contains transactions made by credit cards in September 2013 by european cardholders. This dataset present transactions that occurred in two days, where we have 492 frauds out of 284,807…
355 runs0 likes55 downloads55 reach12 impact
284807 instances - 31 features - 2 classes - 0 missing values
1. Title: Pima Indians Diabetes Database 2. Sources: (a) Original owners: National Institute of Diabetes and Digestive and Kidney Diseases (b) Donor of database: Vincent Sigillito…
200814 runs5 likes78 downloads83 reach7 impact
768 instances - 9 features - 2 classes - 0 missing values
Data on predicting clicks on ads in a search engine.
0 runs0 likes8 downloads8 reach6 impact
1496391 instances - 12 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 reach8 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…
772 runs0 likes14 downloads14 reach8 impact
2310 instances - 20 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 reach7 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,…
109963 runs1 likes19 downloads20 reach20 impact
15545 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…
169 runs0 likes8 downloads8 reach9 impact
600 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…
772 runs0 likes7 downloads7 reach7 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…
140 runs0 likes6 downloads6 reach8 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…
1149 runs0 likes10 downloads10 reach7 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…
781 runs0 likes12 downloads12 reach8 impact
5473 instances - 11 features - 2 classes - 0 missing values
No data.
747 runs0 likes7 downloads7 reach8 impact
369 instances - 9 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…
113757 runs0 likes15 downloads15 reach19 impact
1458 instances - 38 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 runs1 likes9 downloads10 reach8 impact
990 instances - 14 features - 2 classes - 0 missing values