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

Internet

https://www.mdpi.com/2076-3417/11/6/2823

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