Benchmark for filter methods for feature selection in high-dimensional classification data

Volume: 143, Pages: 106839 - 106839
Published: Mar 1, 2020
Abstract
Feature selection is one of the most fundamental problems in machine learning and has drawn increasing attention due to high-dimensional data sets emerging from different fields like bioinformatics. For feature selection, filter methods play an important role, since they can be combined with any machine learning model and can heavily reduce run time of machine learning algorithms. The aim of the analyses is to review how different filter methods...
Paper Details
Title
Benchmark for filter methods for feature selection in high-dimensional classification data
Published Date
Mar 1, 2020
Volume
143
Pages
106839 - 106839
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