Subsampling of the dataset riccardo (41161) with seed=0 args.nrows=2000 args.ncols=100 args.nclasses=10 args.no_stratify=True Generated with the following source code: ```python def subsample( self,…
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2000 instances - 101 features - 2 classes - 0 missing values
Subsampling of the dataset guillermo (41159) with seed=0 args.nrows=2000 args.ncols=100 args.nclasses=10 args.no_stratify=True Generated with the following source code: ```python def subsample( self,…
0 runs0 likes0 downloads0 reach0 impact
2000 instances - 101 features - 2 classes - 0 missing values
Subsampling of the dataset guillermo (41159) with seed=1 args.nrows=2000 args.ncols=100 args.nclasses=10 args.no_stratify=True Generated with the following source code: ```python def subsample( self,…
0 runs0 likes0 downloads0 reach0 impact
2000 instances - 101 features - 2 classes - 0 missing values
Subsampling of the dataset guillermo (41159) with seed=2 args.nrows=2000 args.ncols=100 args.nclasses=10 args.no_stratify=True Generated with the following source code: ```python def subsample( self,…
0 runs0 likes0 downloads0 reach0 impact
2000 instances - 101 features - 2 classes - 0 missing values
Subsampling of the dataset riccardo (41161) with seed=1 args.nrows=2000 args.ncols=100 args.nclasses=10 args.no_stratify=True Generated with the following source code: ```python def subsample( self,…
0 runs0 likes0 downloads0 reach0 impact
2000 instances - 101 features - 2 classes - 0 missing values
Subsampling of the dataset riccardo (41161) with seed=2 args.nrows=2000 args.ncols=100 args.nclasses=10 args.no_stratify=True Generated with the following source code: ```python def subsample( self,…
0 runs0 likes0 downloads0 reach0 impact
2000 instances - 101 features - 2 classes - 0 missing values
Dataset used in the tabular data benchmark https://github.com/LeoGrin/tabular-benchmark, transformed in the same way. This dataset belongs to the "classification on numerical features" benchmark.…
0 runs0 likes0 downloads0 reach0 impact
3434 instances - 420 features - 2 classes - 0 missing values
Dataset used in the tabular data benchmark https://github.com/LeoGrin/tabular-benchmark, transformed in the same way. This dataset belongs to the "classification on numerical features" benchmark.…
0 runs0 likes0 downloads0 reach0 impact
13272 instances - 21 features - 2 classes - 0 missing values
Dataset used in the tabular data benchmark https://github.com/LeoGrin/tabular-benchmark, transformed in the same way. This dataset belongs to the "classification on numerical features" benchmark.…
0 runs0 likes0 downloads0 reach0 impact
57580 instances - 55 features - 2 classes - 0 missing values
Dataset used in the tabular data benchmark https://github.com/LeoGrin/tabular-benchmark, transformed in the same way. This dataset belongs to the "classification on numerical features" benchmark.…
0 runs0 likes0 downloads0 reach0 impact
20634 instances - 9 features - 2 classes - 0 missing values
Dataset used in the tabular data benchmark https://github.com/LeoGrin/tabular-benchmark, transformed in the same way. This dataset belongs to the "classification on numerical features" benchmark.…
0 runs0 likes0 downloads0 reach0 impact
71090 instances - 8 features - 2 classes - 0 missing values
Dataset used in the tabular data benchmark https://github.com/LeoGrin/tabular-benchmark, transformed in the same way. This dataset belongs to the "classification on numerical features" benchmark.…
0 runs0 likes0 downloads0 reach0 impact
10000 instances - 23 features - 2 classes - 0 missing values
Dataset used in the tabular data benchmark https://github.com/LeoGrin/tabular-benchmark, transformed in the same way. This dataset belongs to the "classification on numerical features" benchmark.…
0 runs0 likes0 downloads0 reach0 impact
16714 instances - 11 features - 2 classes - 0 missing values
Dataset used in the tabular data benchmark https://github.com/LeoGrin/tabular-benchmark, transformed in the same way. This dataset belongs to the "classification on numerical features" benchmark.…
0 runs0 likes0 downloads0 reach0 impact
20634 instances - 9 features - 2 classes - 0 missing values
Dataset used in the tabular data benchmark https://github.com/LeoGrin/tabular-benchmark, transformed in the same way. This dataset belongs to the "classification on numerical features" benchmark.…
0 runs0 likes0 downloads0 reach0 impact
10000 instances - 23 features - 2 classes - 0 missing values
Dataset used in the tabular data benchmark https://github.com/LeoGrin/tabular-benchmark, transformed in the same way. This dataset belongs to the "classification on numerical features" benchmark.…
0 runs0 likes0 downloads0 reach0 impact
16714 instances - 11 features - 2 classes - 0 missing values
Data from the PASCAL Challenge 2008 as available on the LibSVM repository ## Description Preprocessing: The raw data set (epsilon_train) is instance-wisely scaled to unit length and split into two…
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500000 instances - 2001 features - 2 classes - 0 missing values
Improve on the state of the art in credit scoring by predicting the probability that somebody will experience financial distress in the next two years. ## Description Banks play a crucial role in…
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150000 instances - 11 features - 2 classes - 33655 missing values
Binarized version of the California Housing Dataset This dataset was obtained from Luis Torgo's collection of regression datasets. It was binarized to serve as the original, unprocessed date for the…
0 runs0 likes0 downloads0 reach0 impact
20640 instances - 9 features - 2 classes - 0 missing values
The weather problem is a tiny dataset that we will use repeatedly to illustrate machine learning methods. Entirely fictitious, it supposedly concerns the conditions that are suitable for playing some…
0 runs0 likes0 downloads0 reach0 impact
14 instances - 5 features - 2 classes - 0 missing values
The weather problem is a tiny dataset that we will use repeatedly to illustrate machine learning methods. Entirely fictitious, it supposedly concerns the conditions that are suitable for playing some…
0 runs0 likes0 downloads0 reach0 impact
14 instances - 5 features - 2 classes - 0 missing values
The weather problem is a tiny dataset that we will use repeatedly to illustrate machine learning methods. Entirely fictitious, it supposedly concerns the conditions that are suitable for playing some…
0 runs0 likes0 downloads0 reach0 impact
14 instances - 5 features - 2 classes - 0 missing values
# Space Shuttle Autolanding Domain NASA: Mr. Roger Burke's autolander design team ##### Past Usage: (several, it appears) Example: Michie,D. (1988). The Fifth Generation's Unbridged Gap. In Rolf…
1466 runs0 likes0 downloads0 reach0 impact
15 instances - 7 features - 2 classes - 26 missing values
Prediction task is to determine whether a person makes over 50K a year. Extraction was done by Barry Becker from the 1994 Census database. A set of reasonably clean records was extracted using the…
2671 runs0 likes0 downloads0 reach0 impact
48842 instances - 15 features - 2 classes - 6465 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 runs0 likes0 downloads0 reach0 impact
106 instances - 58 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 likes0 downloads0 reach0 impact
3107 instances - 7 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
118 runs0 likes0 downloads0 reach0 impact
195 instances - 11 features - 2 classes - 2 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
670 runs0 likes0 downloads0 reach0 impact
62 instances - 8 features - 2 classes - 8 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
575 runs0 likes0 downloads0 reach0 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…
746 runs0 likes0 downloads0 reach0 impact
1024 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…
739 runs0 likes0 downloads0 reach0 impact
500 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…
594 runs0 likes0 downloads0 reach0 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…
822 runs0 likes0 downloads0 reach0 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…
718 runs0 likes0 downloads0 reach0 impact
159 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…
1013 runs0 likes0 downloads0 reach0 impact
163 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…
777 runs0 likes0 downloads0 reach0 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…
758 runs0 likes0 downloads0 reach0 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…
615 runs0 likes0 downloads0 reach0 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…
762 runs0 likes0 downloads0 reach0 impact
8192 instances - 33 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 likes0 downloads0 reach0 impact
194 instances - 33 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 likes0 downloads0 reach0 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…
856 runs0 likes0 downloads0 reach0 impact
209 instances - 7 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
602 runs0 likes0 downloads0 reach0 impact
13750 instances - 41 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
1136 runs0 likes0 downloads0 reach0 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…
708 runs0 likes0 downloads0 reach0 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…
790 runs0 likes0 downloads0 reach0 impact
159 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…
753 runs0 likes0 downloads0 reach0 impact
8192 instances - 13 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
1190 runs0 likes0 downloads0 reach0 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…
764 runs0 likes0 downloads0 reach0 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…
1058 runs0 likes0 downloads0 reach0 impact
167 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…
748 runs0 likes0 downloads0 reach0 impact
500 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…
754 runs0 likes0 downloads0 reach0 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…
700 runs0 likes0 downloads0 reach0 impact
294 instances - 14 features - 2 classes - 782 missing values
Binarized version of the original data set (see version 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 likes0 downloads0 reach0 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…
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…
1252 runs0 likes0 downloads0 reach0 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…
107 runs0 likes0 downloads0 reach0 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…
963 runs0 likes0 downloads0 reach0 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…
730 runs0 likes0 downloads0 reach0 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…
759 runs0 likes0 downloads0 reach0 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…
1202 runs0 likes0 downloads0 reach0 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…
788 runs0 likes0 downloads0 reach0 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 likes0 downloads0 reach0 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…
985 runs0 likes0 downloads0 reach0 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…
816 runs0 likes0 downloads0 reach0 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…
792 runs0 likes0 downloads0 reach0 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…
785 runs0 likes0 downloads0 reach0 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…
779 runs0 likes0 downloads0 reach0 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…
733 runs0 likes0 downloads0 reach0 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…
773 runs0 likes0 downloads0 reach0 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…
1767 runs0 likes0 downloads0 reach0 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…
775 runs0 likes0 downloads0 reach0 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…
721 runs0 likes0 downloads0 reach0 impact
60 instances - 8 features - 2 classes - 0 missing values
Dataset from the Agnostic Learning vs. Prior Knowledge Challenge (http://www.agnostic.inf.ethz.ch), which consisted of 5 different datasets (SYLVA, GINA, NOVA, HIVA, ADA). The purpose of the challenge…
69235 runs0 likes0 downloads0 reach0 impact
3468 instances - 971 features - 2 classes - 0 missing values
Datasets from the Agnostic Learning vs. Prior Knowledge Challenge (http://www.agnostic.inf.ethz.ch) Dataset from: http://www.agnostic.inf.ethz.ch/datasets.php Modified by TunedIT (converted to ARFF…
406 runs0 likes0 downloads0 reach0 impact
4229 instances - 1618 features - 2 classes - 0 missing values
Datasets from the Agnostic Learning vs. Prior Knowledge Challenge (http://www.agnostic.inf.ethz.ch) Dataset from: http://www.agnostic.inf.ethz.ch/datasets.php Modified by TunedIT (converted to ARFF…
486 runs0 likes0 downloads0 reach0 impact
14395 instances - 109 features - 2 classes - 0 missing values
Datasets from the Agnostic Learning vs. Prior Knowledge Challenge (http://www.agnostic.inf.ethz.ch) Dataset from: http://www.agnostic.inf.ethz.ch/datasets.php Modified by TunedIT (converted to ARFF…
548 runs0 likes0 downloads0 reach0 impact
3468 instances - 785 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 likes0 downloads0 reach0 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,…
109967 runs0 likes0 downloads0 reach0 impact
15545 instances - 6 features - 2 classes - 0 missing values
Datasets from the Agnostic Learning vs. Prior Knowledge Challenge (http://www.agnostic.inf.ethz.ch) Dataset from: http://www.agnostic.inf.ethz.ch/datasets.php Modified by TunedIT (converted to ARFF…
778 runs0 likes0 downloads0 reach0 impact
4562 instances - 15 features - 2 classes - 88 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…
146026 runs1 likes18 downloads19 reach27 impact
1563 instances - 38 features - 2 classes - 0 missing values
No data.
747 runs0 likes0 downloads0 reach0 impact
369 instances - 9 features - 2 classes - 0 missing values
1. Title: Haberman's Survival Data 2. Sources: (a) Donor: Tjen-Sien Lim (limt@stat.wisc.edu) (b) Date: March 4, 1999 3. Past Usage: 1. Haberman, S. J. (1976). Generalized Residuals for Log-Linear…
3243 runs0 likes0 downloads0 reach0 impact
306 instances - 4 features - 2 classes - 0 missing values
Attribute information: ``` sick, negative. | classes age: continuous. sex: M, F. on thyroxine: f, t. query on thyroxine: f, t. on antithyroid medication: f, t. sick: f, t. pregnant: f, t. thyroid…
19950 runs0 likes0 downloads0 reach0 impact
3772 instances - 30 features - 2 classes - 6064 missing values
NAME: Sonar, Mines vs. Rocks SUMMARY: This is the data set used by Gorman and Sejnowski in their study of the classification of sonar signals using a neural network [1]. The task is to train a network…
2372 runs0 likes0 downloads0 reach0 impact
208 instances - 61 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…
203503 runs0 likes0 downloads0 reach0 impact
768 instances - 9 features - 2 classes - 0 missing values
SPAM E-mail Database The "spam" concept is diverse: advertisements for products/websites, make money fast schemes, chain letters, pornography... Our collection of spam e-mails came from our postmaster…
162017 runs0 likes0 downloads0 reach0 impact
4601 instances - 58 features - 2 classes - 0 missing values
See [https://github.com/slds-lmu/paper_2023_ci_for_ge](https://github.com/slds-lmu/paper_2023_ci_for_ge) for a description.
0 runs0 likes0 downloads0 reach0 impact
5100000 instances - 11 features - 2 classes - 0 missing values
See [https://github.com/slds-lmu/paper_2023_ci_for_ge](https://github.com/slds-lmu/paper_2023_ci_for_ge) for a description.
0 runs0 likes0 downloads0 reach0 impact
5100000 instances - 15 features - 2 classes - 0 missing values
See [https://github.com/slds-lmu/paper_2023_ci_for_ge](https://github.com/slds-lmu/paper_2023_ci_for_ge) for a description.
0 runs0 likes0 downloads0 reach0 impact
5100000 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…
511 runs0 likes0 downloads0 reach0 impact
185 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…
680 runs0 likes0 downloads0 reach0 impact
1945 instances - 19 features - 2 classes - 1133 missing values
Binarized version of the original data set (see version 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 likes0 downloads0 reach0 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…
714 runs0 likes4 downloads4 reach15 impact
303 instances - 14 features - 2 classes - 6 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
802 runs0 likes0 downloads0 reach0 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 likes0 downloads0 reach0 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…
620 runs0 likes10 downloads10 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…
806 runs0 likes0 downloads0 reach0 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…
791 runs0 likes0 downloads0 reach0 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…
812 runs0 likes0 downloads0 reach0 impact
250 instances - 26 features - 2 classes - 0 missing values