Feature Selection and Feature Extraction in Pattern Analysis: A Literature Review
Machine Learning
2019-05-09 v1 Artificial Intelligence
Computer Vision and Pattern Recognition
Machine Learning
Abstract
Pattern analysis often requires a pre-processing stage for extracting or selecting features in order to help the classification, prediction, or clustering stage discriminate or represent the data in a better way. The reason for this requirement is that the raw data are complex and difficult to process without extracting or selecting appropriate features beforehand. This paper reviews theory and motivation of different common methods of feature selection and extraction and introduces some of their applications. Some numerical implementations are also shown for these methods. Finally, the methods in feature selection and extraction are compared.
Cite
@article{arxiv.1905.02845,
title = {Feature Selection and Feature Extraction in Pattern Analysis: A Literature Review},
author = {Benyamin Ghojogh and Maria N. Samad and Sayema Asif Mashhadi and Tania Kapoor and Wahab Ali and Fakhri Karray and Mark Crowley},
journal= {arXiv preprint arXiv:1905.02845},
year = {2019}
}
Comments
14 pages, 1 figure, 2 tables, survey (literature review) paper