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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…
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
* Dataset Title: Wall-Following Robot Navigation Data Data Set (version with 4 Attributes) * Abstract: The data were collected as the SCITOS G5 robot navigates through the room following the wall in a…
138 runs1 likes6 downloads7 reach8 impact
5456 instances - 5 features - 4 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…
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…
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…
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…
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…
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
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). 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…
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…
777 runs0 likes8 downloads8 reach8 impact
625 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…
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
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…
781 runs0 likes12 downloads12 reach8 impact
5473 instances - 11 features - 2 classes - 0 missing values
Jarkko Salojarvi, Kai Puolamaki, Jaana Simola, Lauri Kovanen, Ilpo Kojo, Samuel Kaski. Inferring Relevance from Eye Movements: Feature Extraction. Helsinki University of Technology, Publications in…
440 runs0 likes11 downloads11 reach8 impact
10936 instances - 28 features - 3 classes - 0 missing values
No data.
747 runs0 likes7 downloads7 reach8 impact
369 instances - 9 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
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…
676 runs0 likes13 downloads13 reach8 impact
10992 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…
815 runs0 likes8 downloads8 reach8 impact
336 instances - 8 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 reach8 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…
775 runs0 likes13 downloads13 reach8 impact
2178 instances - 4 features - 2 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…
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…
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 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…
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
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…
65 runs0 likes1 downloads1 reach7 impact
321 instances - 10937 features - 2 classes - 0 missing values
Pittsburgh bridges This version is derived from version 1 by removing all instances with missing values in the last (target) attribute. The bridges dataset is originally not a classification dataset,…
31 runs0 likes1 downloads1 reach7 impact
105 instances - 13 features - 6 classes - 61 missing values
Pittsburgh bridges This version is derived from version 2 (the discretized version) by removing all instances with missing values in the last (target) attribute. The bridges dataset is originally not…
31 runs0 likes2 downloads2 reach7 impact
105 instances - 13 features - 6 classes - 61 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 likes2 downloads2 reach7 impact
92 instances - 6 features - 0 classes - 26 missing values
Om algos te testen
74 runs0 likes5 downloads5 reach7 impact
14240 instances - 31 features - 2 classes - 0 missing values
Andrew V Uzilov, Joshua M Keegan, and David H Mathews. Detection of non-coding RNAs on the basis of predicted secondary structure formation free energy change. BMC Bioinformatics, 7(173), 2006. This…
31 runs0 likes10 downloads10 reach7 impact
488565 instances - 9 features - 2 classes - 0 missing values
Data originating from the book "Analyzing Categorical Data" by Jeffrey S. Simonoff.
1085 runs0 likes9 downloads9 reach7 impact
50 instances - 5 features - 2 classes - 0 missing values
Source: Ashwin Srinivasan Department of Statistics and Data Modeling University of Strathclyde Glasgow Scotland UK ross '@' uk.ac.turing The original Landsat data for this database was generated from…
1 runs1 likes6 downloads7 reach7 impact
6435 instances - 37 features - 0 classes - 0 missing values
University of Sao Paulo, School of Art, Sciences and Humanities, Sao Paulo, SP, Brazil ### LIBRAS Movement Database LIBRAS, acronym of the Portuguese name "LIngua BRAsileira de Sinais", is the…
0 runs0 likes4 downloads4 reach7 impact
360 instances - 91 features - 0 classes - 0 missing values
This is a 10% stratified subsample of the data from the 1999 ACM KDD Cup (http://www.sigkdd.org/kddcup/index.php). Modified by TunedIT (converted to ARFF format)…
25 runs1 likes35 downloads36 reach7 impact
494020 instances - 42 features - 23 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…
66 runs0 likes1 downloads1 reach7 impact
386 instances - 10937 features - 2 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 reach7 impact
581012 instances - 55 features - 2 classes - 0 missing values
The goal of this challenge is to expose the research community to real world datasets of interest to 4Paradigm. All datasets are formatted in a uniform way, though the type of data might differ. The…
0 runs0 likes2 downloads2 reach7 impact
10000 instances - 2001 features - 5 classes - 0 missing values
The goal of this challenge is to expose the research community to real world datasets of interest to 4Paradigm. All datasets are formatted in a uniform way, though the type of data might differ. The…
0 runs0 likes0 downloads0 reach7 impact
8237 instances - 801 features - 7 classes - 0 missing values
The goal of this challenge is to expose the research community to real world datasets of interest to 4Paradigm. All datasets are formatted in a uniform way, though the type of data might differ. The…
5 runs0 likes0 downloads0 reach7 impact
10000 instances - 7201 features - 10 classes - 0 missing values
The goal of this challenge is to expose the research community to real world datasets of interest to 4Paradigm. All datasets are formatted in a uniform way, though the type of data might differ. The…
6 runs0 likes1 downloads1 reach7 impact
83733 instances - 55 features - 4 classes - 0 missing values
The goal of this challenge is to expose the research community to real world datasets of interest to 4Paradigm. All datasets are formatted in a uniform way, though the type of data might differ. The…
7 runs0 likes1 downloads1 reach7 impact
58310 instances - 181 features - 10 classes - 0 missing values
Citation Request: This dataset is public available for research. The details are described in [Cortez et al., 2009]. Please include this citation if you plan to use this database: P. Cortez, A.…
64 runs1 likes5 downloads6 reach7 impact
4898 instances - 12 features - 7 classes - 0 missing values
Costa madre 1
90 runs0 likes6 downloads6 reach7 impact
296 instances - 38 features - 2 classes - 0 missing values
### Description ### This dataset is part of a collection datasets based on the game "Jungle Chess" (a.k.a. Dou Shou Qi). For a description of the rules, please refer to the paper (link attached). The…
4700 runs0 likes2 downloads2 reach7 impact
44819 instances - 7 features - 3 classes - 0 missing values
The goal of this challenge is to expose the research community to real world datasets of interest to 4Paradigm. All datasets are formatted in a uniform way, though the type of data might differ. The…
0 runs0 likes1 downloads1 reach7 impact
425240 instances - 79 features - 2 classes - 2734000 missing values
The data is cleaned, regularized and encrypted global equity data. The first 21 columns (feature1 - feature21) are features, and target is the binary class you’re trying to predict.
882 runs1 likes2 downloads3 reach7 impact
96320 instances - 22 features - 2 classes - 0 missing values
Multi-label dataset. The UC Berkeley enron4 dataset represents a subset of the original enron5 dataset and consists of 1684 cases of emails with 21 labels and 1001 predictor variables.
1 runs0 likes3 downloads3 reach7 impact
1702 instances - 1054 features - 2 classes - 0 missing values