Evolving multi-label classification rules by exploiting high-order label correlations
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TL;DR: In this article, the label powerset (LP) strategy is employed and a prediction aggregation is utilized that improves the prediction capability of the LP method in the presence of unseen labelsets.
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About: This article is published in Neurocomputing. The article was published on 05 Dec 2020. and is currently open access. The article focuses on the topics: Multi-label classification & Supervised learning.
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An overview of LCS research from 2020 to 2021
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Multi-label classification with local pairwise and high-order label correlations using graph partitioning
TL;DR: A rule-based evolutionary multi-label classification method is proposed that incorporates the local label correlations through the high-order label subsets and pairwise dependencies and has shown the highest average rank along multiple metrics.
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