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Optimal Linear Combination of Classifiers

arXiv 2103.01109 ↗First posted 1 Mar 2021cs.LG cs.AIcited by 0

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Abstract (arXiv)

The question of whether to use one classifier or a combination of classifiers is a central topic in Machine Learning. We propose here a method for finding an optimal linear combination of classifiers derived from a bias-variance framework for the classification task.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 1 of its 4 references that are in the map. First posted on arXiv 1 Mar 2021.

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References · 1

  1. 2019A Note on Posterior Probability Estimation for Classifierscited by 1

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