EvoSplit: An Evolutionary Approach to Split a Multi-Label Data Set into Disjoint Subsets

EvoSplit: An Evolutionary Approach to Split a Multi-Label Data Set into Disjoint Subsets

This paper presents a new evolutionary approach, EvoSplit, for the distribution of multi-label data sets into disjoint subsets for supervised machine learning. Currently, data set providers either divide a data set randomly or using iterative stratification, a method that aims to maintain the label...

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Bibliographic Details
Main Author:	Francisco Florez-Revuelta
Format:	Article
Language:	English
Published:	MDPI AG 2021-03-01
Series:	Applied Sciences
Subjects:	multi-label data sets supervised learning machine learning evolutionary computation big data applications
Online Access:	https://www.mdpi.com/2076-3417/11/6/2823

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