2022, Volume 23, Issue 10
Frontiers of Information Technology & Electronic Engineering >> 2022, Volume 23, Issue 10 doi: 10.1631/FITEE.2100569
Feature selection techniques for microarray datasets: a comprehensive review, taxonomy, and future directions
印度信息技术学院计算科学与工程系，印度蒂鲁吉拉伯利市，620012
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Abstract
For optimal results, retrieving a relevant feature from a has become a hot topic for researchers involved in the study of (FS) techniques. The aim of this review is to provide a thorough description of various, recent FS techniques. This review also focuses on the techniques proposed for s to work on multiclass classification problems and on different ways to enhance the performance of learning algorithms. We attempt to understand and resolve the imbalance problem of datasets to substantiate the work of researchers working on s. An analysis of the literature paves the way for comprehending and highlighting the multitude of challenges and issues in finding the optimal feature subset using various FS techniques. A case study is provided to demonstrate the process of implementation, in which three microarray cancer datasets are used to evaluate the classification accuracy and convergence ability of several wrappers and hybrid algorithms to identify the optimal feature subset.
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