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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…
772 runs0 likes8 downloads8 reach15 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…
762 runs0 likes13 downloads13 reach15 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…
744 runs0 likes12 downloads12 reach15 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…
104 runs0 likes7 downloads7 reach15 impact
1302 instances - 34 features - 2 classes - 7830 missing values
Asteroid Dataset
0 runs0 likes1 downloads1 reach8 impact
126131 instances - 34 features - 2 classes - 99 missing values
Phishing website 1
0 runs0 likes0 downloads0 reach2 impact
11055 instances - 31 features - 0 classes - 0 missing values
# Achieved Frames per Second (FPS) in video games This dataset contains FPS measurement of video games executed on computers. Each row of the dataset describes the outcome of FPS measurement (outcome…
0 runs0 likes0 downloads0 reach0 impact
425833 instances - 45 features - 0 classes - 1299988 missing values
Context It is important that credit card companies are able to recognize fraudulent credit card transactions so that customers are not charged for items that they did not purchase. Content The…
0 runs1 likes7 downloads8 reach8 impact
284807 instances - 31 features - 0 classes - 0 missing values
Om algos te testen
74 runs0 likes6 downloads6 reach15 impact
14240 instances - 31 features - 2 classes - 0 missing values
Multivariate regression data set from: https://link.springer.com/article/10.1007%2Fs10994-016-5546-z : The Water Quality dataset (Dzeroski et al. 2000) has 14 target attributes that refer to the…
0 runs0 likes0 downloads0 reach9 impact
1060 instances - 30 features - classes - 0 missing values
The YouTube personality dataset consists of a collection of behavorial features, speech transcriptions, and personality impression scores for a set of 404 YouTube vloggers that explicitly show…
0 runs0 likes0 downloads0 reach9 impact
404 instances - 31 features - classes - 0 missing values
The sick dataset from the OpenCC18 with all categorical data label encoded so all data is numeric
0 runs0 likes0 downloads0 reach8 impact
3772 instances - 30 features - classes - 0 missing values
Embedding of atoms for HIV inhibitors dataser
0 runs0 likes0 downloads0 reach7 impact
1069964 instances - 30 features - classes - 0 missing values
Embedding of molecules bonds in HIV inhibitors dataset
0 runs0 likes0 downloads0 reach7 impact
1151940 instances - 30 features - classes - 0 missing values
The YouTube personality dataset consists of a collection of behavorial features, speech transcriptions, and personality impression scores for a set of 404 YouTube vloggers that explicitly show…
0 runs0 likes1 downloads1 reach9 impact
404 instances - 31 features - 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 runs1 likes56 downloads57 reach20 impact
284807 instances - 31 features - 2 classes - 0 missing values
Context It is important that credit card companies are able to recognize fraudulent credit card transactions so that customers are not charged for items that they did not purchase. Content The…
0 runs1 likes2 downloads3 reach8 impact
284807 instances - 31 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…
226562 runs4 likes37 downloads41 reach27 impact
569 instances - 31 features - 2 classes - 0 missing values
Data Set Information: The data has been produced using Monte Carlo simulations. The first 21 features (columns 2-22) are kinematic properties measured by the particle detectors in the accelerator. The…
0 runs1 likes5 downloads6 reach16 impact
98050 instances - 29 features - 0 classes - 9 missing values
Source: 1. Olcay KURSUN, PhD., Istanbul University, Department of Computer Engineering, 34320, Istanbul, Turkey Phone: +90 (212) 473 7070 - 17827 Email: okursun '@' istanbul.edu.tr 2. Betul ERDOGDU…
0 runs0 likes3 downloads3 reach11 impact
1039 instances - 29 features - classes - 0 missing values
Sick dataset from the opencc18 with all textual binary variables label encoded.
1 runs0 likes2 downloads2 reach9 impact
3772 instances - 30 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
--Title: AR4 /Software Defect Prediction --Date: February, 4th, 2009 --Data from a Turkish white-goods manufacturer --Donated by: Software Research Laboratory (Softlab), Bogazici University, Istanbul,…
794 runs1 likes13 downloads14 reach14 impact
107 instances - 30 features - 2 classes - 0 missing values
--Title: AR6 /Software Defect Prediction --Date: February, 4th, 2009 --Data from a Turkish white-goods manufacturer --Donated by: Software Research Laboratory (Softlab), Bogazici University, Istanbul,…
789 runs0 likes9 downloads9 reach14 impact
101 instances - 30 features - 2 classes - 0 missing values
--Title: AR5 / Software Defect Prediction --Date: February, 4th, 2009 --Data from a Turkish white-goods manufacturer --Donated by: Software Research Laboratory (Softlab), Bogazici University,…
726 runs0 likes9 downloads9 reach14 impact
36 instances - 30 features - 2 classes - 0 missing values
--Title: AR3 /Software Defect Prediction --Date: February, 4th, 2009 --Data from a Turkish white-goods manufacturer --Donated by: Software Research Laboratory (Softlab), Bogazici University, Istanbul,…
718 runs0 likes5 downloads5 reach14 impact
63 instances - 30 features - 2 classes - 0 missing values
The task consists of Learning Quantitative Structure Activity Relationships (QSARs). The Inhibition of Dihydrofolate Reductase by Pyrimidines.The data are described in: King, Ross .D., Muggleton,…
6 runs0 likes2 downloads2 reach9 impact
74 instances - 28 features - 0 classes - 0 missing values
This is a smaller version of the original dataset, containing 1M rows. ### Attribute Information * The first column is the class label (1 for signal, 0 for background) * 21 low-level features…
0 runs0 likes0 downloads0 reach0 impact
1000000 instances - 29 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
Source: 1. Muhammad Naeem, Centre of Research in Data Engineering(CORDE) & Department of Computer Science, MAJU Islamabad Pakistan(naeems.naeem '@' gmail.com). 2. Sohail Asghar, Director/Associate…
0 runs0 likes1 downloads1 reach11 impact
65554 instances - 29 features - classes - 0 missing values
Testing dataset
0 runs0 likes1 downloads1 reach3 impact
134731 instances - 31 features - 2 classes - 0 missing values
Public procurement data for the European Economic Area, Switzerland, and the Macedonia. 2015
0 runs0 likes1 downloads1 reach8 impact
565163 instances - 75 features - 0 classes - 15247061 missing values
__Changes w.r.t. version 1: included one target factor with 7 levels as target variable for the classification. Also deleted the previous 7 binary target variables.__ A dataset of steel plates'…
9007 runs1 likes3 downloads4 reach15 impact
1941 instances - 28 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…
10 runs0 likes2 downloads2 reach18 impact
65196 instances - 28 features - 100 classes - 0 missing values
White Clover Persistence Trials Data source: Ian Tarbotton AgResearch, Whatawhata Research Centre, Hamilton, New Zealand The objective was to determine the mechanisms which influence the persistence…
858 runs0 likes5 downloads5 reach15 impact
63 instances - 32 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…
734 runs0 likes6 downloads6 reach14 impact
74 instances - 28 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…
732 runs0 likes5 downloads5 reach14 impact
63 instances - 32 features - 2 classes - 0 missing values
Multivariate regression data set from: https://link.springer.com/article/10.1007%2Fs10994-016-5546-z : This is a pre-processed version of the dataset used in Kaggles See Click Predict Fix competition…
0 runs0 likes0 downloads0 reach9 impact
1137 instances - 26 features - classes - 9255 missing values
This dataset is an artificial simulation of the Duffing system with random changes from the chaotic to the non-chaotic regime at different noise levels.
0 runs0 likes0 downloads0 reach8 impact
2493200 instances - 26 features - classes - 0 missing values
Multivariate regression data set from: https://link.springer.com/article/10.1007%2Fs10994-016-5546-z : This is a pre-processed version of the dataset used in Kaggles See Click Predict Fix competition…
0 runs0 likes0 downloads0 reach9 impact
1137 instances - 26 features - classes - 9255 missing values
The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as…
0 runs0 likes0 downloads0 reach13 impact
500 instances - 26 features - 0 classes - 0 missing values
Training dataset of the 'Porto Seguros Safe Driver Prediction' Kaggle challenge [https://www.kaggle.com/c/porto-seguro-safe-driver-prediction]. The goal was to predict whether a driver will file an…
0 runs0 likes0 downloads0 reach0 impact
595212 instances - 58 features - 2 classes - 846458 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 reach16 impact
425240 instances - 79 features - 2 classes - 2734000 missing values
The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as…
0 runs0 likes0 downloads0 reach13 impact
100 instances - 26 features - 0 classes - 0 missing values
The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as…
0 runs0 likes0 downloads0 reach13 impact
250 instances - 26 features - 0 classes - 0 missing values
The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as…
0 runs0 likes0 downloads0 reach13 impact
100 instances - 26 features - 0 classes - 0 missing values
The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as…
0 runs0 likes1 downloads1 reach13 impact
1000 instances - 26 features - 0 classes - 0 missing values
The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as…
0 runs0 likes1 downloads1 reach13 impact
1000 instances - 26 features - 0 classes - 0 missing values
The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as…
0 runs0 likes0 downloads0 reach13 impact
500 instances - 26 features - 0 classes - 0 missing values
The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as…
0 runs0 likes0 downloads0 reach13 impact
250 instances - 26 features - 0 classes - 0 missing values
The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as…
0 runs0 likes0 downloads0 reach13 impact
100 instances - 26 features - 0 classes - 0 missing values
The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as…
0 runs0 likes0 downloads0 reach13 impact
100 instances - 26 features - 0 classes - 0 missing values
The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as…
0 runs0 likes1 downloads1 reach13 impact
1000 instances - 26 features - 0 classes - 0 missing values
The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as…
0 runs0 likes0 downloads0 reach13 impact
500 instances - 26 features - 0 classes - 0 missing values
The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as…
0 runs0 likes1 downloads1 reach13 impact
250 instances - 26 features - 0 classes - 0 missing values
The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as…
0 runs0 likes0 downloads0 reach13 impact
250 instances - 26 features - 0 classes - 0 missing values
The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as…
0 runs0 likes0 downloads0 reach13 impact
500 instances - 26 features - 0 classes - 0 missing values
The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as…
1 runs0 likes1 downloads1 reach13 impact
500 instances - 26 features - 0 classes - 0 missing values
The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as…
0 runs0 likes2 downloads2 reach13 impact
1000 instances - 26 features - 0 classes - 0 missing values
The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as…
0 runs0 likes0 downloads0 reach13 impact
250 instances - 26 features - 0 classes - 0 missing values
The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as…
0 runs0 likes1 downloads1 reach13 impact
1000 instances - 26 features - 0 classes - 0 missing values
The Friedman datasets are 80 artificially generated datasets originating from: J.H. Friedman (1999). Stochastic Gradient Boosting The dataset names are coded as…
21 runs0 likes0 downloads0 reach14 impact
100 instances - 26 features - 0 classes - 0 missing values
No data.
0 runs0 likes0 downloads0 reach16 impact
1000 instances - 25 features - 0 classes - 0 missing values
This is a sesnor data for test it is not complete.
0 runs0 likes4 downloads4 reach11 impact
127591 instances - 27 features - classes - 0 missing values
No data.
0 runs0 likes0 downloads0 reach17 impact
1000 instances - 25 features - 0 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 likes7 downloads7 reach15 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…
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…
791 runs0 likes7 downloads7 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…
789 runs0 likes7 downloads7 reach14 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…
770 runs0 likes8 downloads8 reach14 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…
746 runs0 likes6 downloads6 reach15 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…
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). 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 reach15 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…
776 runs0 likes7 downloads7 reach14 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…
617 runs0 likes11 downloads11 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…
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…
759 runs0 likes6 downloads6 reach15 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…
813 runs0 likes7 downloads7 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…
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). 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…
816 runs0 likes7 downloads7 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…
806 runs0 likes6 downloads6 reach15 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…
775 runs0 likes6 downloads6 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…
792 runs0 likes7 downloads7 reach14 impact
100 instances - 26 features - 2 classes - 0 missing values
The data were collected as the SCITOS G5 robot navigates through the room following the wall in a clockwise direction, for 4 rounds, using 24 ultrasound sensors arranged circularly around its 'waist'.…
25199 runs0 likes21 downloads21 reach34 impact
5456 instances - 25 features - 4 classes - 0 missing values
This is one of 41 drug design datasets. The datasets with 1143 features are formed using Adriana.Code software (www.molecular-networks.com/software/adrianacode). The molecules and outputs are taken…
0 runs0 likes0 downloads0 reach13 impact
16 instances - 24 features - 0 classes - 0 missing values
uci
0 runs0 likes0 downloads0 reach8 impact
30000 instances - 27 features - classes - 0 missing values
Email dataset 1b
0 runs0 likes0 downloads0 reach2 impact
4585 instances - 24 features - 0 classes - 161 missing values
source: An Algorithm Selection Benchmark for the Container Pre-Marshalling Problem (CPMP) authors: K. Tierney and Y. Malitsky (features) / K. Tierney and D. Pacino and S. Voss (algorithms) translator…
20 runs0 likes0 downloads0 reach10 impact
2108 instances - 27 features - 0 classes - 0 missing values
source: An Algorithm Selection Benchmark for the Container Pre-Marshalling Problem (CPMP) authors: K. Tierney and Y. Malitsky (features) / K. Tierney and D. Pacino and S. Voss (algorithms) translator…
14 runs0 likes1 downloads1 reach9 impact
527 instances - 27 features - 4 classes - 0 missing values
#### Competition 1 (preprocessed data) A straight-forward classification task. We provide pre-computed feature vectors for each word in the eye movement trajectory, with class labels. ### Data Set…
440 runs0 likes12 downloads12 reach15 impact
10936 instances - 28 features - 3 classes - 0 missing values
libSVM","AAD group #Dataset from the LIBSVM data repository. Preprocessing: Original data: someone from Germany working with the car industry.
0 runs0 likes1 downloads1 reach16 impact
1243 instances - 23 features - 0 classes - 0 missing values
libSVM","AAD group IJCNN 2001 neural network competition. Slide presentation in IJCNN'01, Ford Research Laboratory, 2001. http://www.geocities.com/ijcnn/nnc_ijcnn01.pdf . #Dataset from the LIBSVM data…
0 runs0 likes8 downloads8 reach17 impact
191681 instances - 23 features - 0 classes - 0 missing values
source: An Algorithm Selection Benchmark for the Container Pre-Marshalling Problem (CPMP) authors: K. Tierney and Y. Malitsky (features) / K. Tierney and D. Pacino and S. Voss (algorithms) translator…
0 runs0 likes1 downloads1 reach8 impact
2108 instances - 24 features - 0 classes - 0 missing values
Data Set Information: This research aimed at the case of customers’ default payments in Taiwan and compares the predictive accuracy of probability of default among six data mining methods. From…
0 runs0 likes1 downloads1 reach7 impact
30000 instances - 24 features - 2 classes - 0 missing values
Water stress dataset for Indian variety of wheat crop: The data consist of a file system-based data of Raj 3765 variety of wheat. There are twenty-four chlorophyll fluorescence images captured every…
0 runs0 likes2 downloads2 reach7 impact
1188 instances - 23 features - 0 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 likes15 downloads16 reach15 impact
195 instances - 23 features - 2 classes - 0 missing values
Source: The dataset was created by Athanasios Tsanas (tsanasthanasis '@' gmail.com) and Max Little (littlem '@' physics.ox.ac.uk) of the University of Oxford, in collaboration with 10 medical centers…
0 runs1 likes2 downloads3 reach11 impact
5875 instances - 22 features - classes - 0 missing values
source: An Algorithm Selection Benchmark for the Container Pre-Marshalling Problem (CPMP) authors: K. Tierney and Y. Malitsky (features) / K. Tierney and D. Pacino and S. Voss (algorithms) translator…
14 runs0 likes0 downloads0 reach8 impact
527 instances - 23 features - 4 classes - 0 missing values