A Review Paper on Feature Selection Methodologies and Their Applications
Shweta Srivastava, Nikita Joshi, Madhvi Gaur · 2014
Abstract:- Feature selection is the process of eliminating features from the data set that are irrelevant with respect to the task to be performed. Feature selection is important for many reasons such as simplification, performance, computational efficiency and feature interpretability. It can be applied to both supervised and unsupervised learning methodologies. Such techniques are able in improving the efficiency of various machine learning algorithms and that of training as well. Feature selection speed up the run time of learning, improves data quality and data understanding.