Feature Selection using Dominant-Set Clustering

Abstract

Feature selection techniques are essentially used in the data analysis tasks, one is frequently dealt with many features. It is computationally expensive to optimize these features that are either redundant and irrelevant. A ton of methods approach to this technique, however, they exist their own limited. In this thesis, dominant-set clustering and multidimensional interaction information method is considered.