• NIJEESHA JOSEPH

Feature selection is the process of eliminating the irrelevant and redundant data from a large dataset. Feature selection mainly three types. They are filter method, Wrapper method and embedded method. Filter method and the wrapper method are the two primary feature selection methods. Feature selection is the preprocessing step in machine learning. In feature selection picks subset from large data set and makes an efficient model for describing the selected subset. Other than selecting the subset, it also have some other advantages, such as dimensionality reduction, adjust the amount of data which are required for learning process and progress in predictive accuracy. The main aim of this work is to get more idea about the concept of feature selection and various feature selection methods.

feature, filter method, wrapper method, embedded method

"A REVIEW : FEATURE SELECTION METHODS FOR TEXT CLASSIFICATION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.38-40, June 2019, Available :http://www.jetir.org/papers/JETIR1907761.pdf

"A REVIEW : FEATURE SELECTION METHODS FOR TEXT CLASSIFICATION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp38-40, June 2019, Available at : http://www.jetir.org/papers/JETIR1907761.pdf