Optimal Linear Combination of Classifiers
arXiv:2103.01109
Abstract
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.
14 pages, 7 figures