Performance Metrics for Feature Selection, Clustering and Classification Algorithms

In recent past, the features selection plays a significant role in machine learning algorithms to improve their performance in terms of increasing the classification accuracy and reducing the classifier building time. Therefore, it is essential to evaluate the performance of the features selection method that is proposed. Moreover, the clustering algorithm also be used some cases in the feature selection process for removing the redundant features from the high-dimensional space therefore identifying the suitable clustering algorithm also be important. Hence, this paper presents the performance metrics for feature selection, clustering and classification algorithms.