Feature decreasing methods using fuzzy rough set based on mutual information
Maryam Shahabi Lotfabadi, Mohd Fairuz Shiratuddin, Kok Wai Wong · 2013
Feature reduction methods are of interest in applications such as content based image and video retrieval. In large multimedia databases, it may not be practical to search through the entire database in order to retrieve the nearest neighbours of a query. Good data structures for similarity search and indexing are needed, and the existing data structures do not scale well for the high dimensional multimedia descriptors. Thus feature reduction is an important step. We investigate the use of rough set for feature reduction. In this paper, we compare three different decreasing methods. They are rough set, fuzzy rough set and fuzzy rough set based on mutual information. From the experimental results, it is shown that the fuzzy rough set based on mutual information can perform better than the other two rough set decreasing methods with increased image retrieval precision.