Feature Selection: A Review and Comparative Study

Feature selection (FS) is an important research topic in the area of data mining and machine learning. FS aims at dealing with high dimensionality problem. It process selecting relevant features removing irrelevant, redundant noisy ones, intending to obtain best performing subset original without any transformation. This paper provides a comprehensive review literature supplement insights recommendations help readers. Moreover, empirical study six well-known feature methods presented so as critically analyzing their applicability.