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A Review Paper on Feature Selection Methodologies and Their Applications


Shweta Srivastava, Nikita Joshi, Madhvi Gaur


Vol. 14  No. 5  pp. 78-81


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


Feature Selection, Supervised, Search strategies, Unsupervised