Comparison of Filter Based Feature Selection Algorithms: an Overview

Feature selection is very much useful to choose a subset of features from data set containing more than 100 to 1000 attributes by eliminating irrelevant features to improve predictive information. Feature selection is the most promising field of research in data mining in which most impressive achievements have been reported. The feature selection influences the predictive accuracy of any data set. Hence, it is essential to study the metrics that are already used in this area. This paper provides the clear insight to different feature selection methods reported in the literature and also compares all methods with each other. The experimental result shows that the feature selection methods provide better result for breast cancer data set.