Ensemble LDA via the modified Cholesky decomposition

Zhenguo Gao, Xinye Wang and Xiaoning Kang

Computational Statistics & Data Analysis, 2023, vol. 188, issue C

Abstract: A binary classification problem in the high-dimensional settings is studied via the ensemble learning with each base classifier constructed from the linear discriminant analysis (LDA), and these base classifiers are integrated by the weighted voting. The precision matrix in the LDA rule is estimated by the modified Cholesky decomposition (MCD), which is able to provide us with a set of precision estimates by considering multiple variable orderings, and hence yield a group of different LDA classifiers. Such available LDA classifiers are then integrated to improve the classification performance. The simulation and the application studies are conducted to demonstrate the merits of the proposed method.

Keywords: Ensemble learning; High-dimensional; Precision matrix; Variable ordering (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:eee:csdana:v:188:y:2023:i:c:s0167947323001342

DOI: 10.1016/j.csda.2023.107823

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