Survey on Methodologies and Techniques Involved in Feature Selection

Feature selection is an important data processing step where irrelevant and redundant attributes are removed for shorter learning time, better accuracy and better comprehensibility. It involves identifying an optimal subset of the most useful features from the original set of features. The efficiency of feature selection algorithm concerns the time required to find a subset of features and the effectiveness is related to the quality of the subset of feature. This paper focuses on the study of different feature selection models, techniques and evaluation measures used for feature selection and their merits and limitations. Then we talk about the different frameworks involved in feature selection and find the gap between them which needs to be bridged so as to improve the feature selection efficiency and performance.