Understanding and Using Rough Set Based Feature Selection: Concepts, Techniques and Applications

Chapter-1: Introduction to Feature Selection

This chapter will discuss feature selection, its background, advantages and practical applications.

Chapter-2: Background

This chapter will explain various Non-RST based Feature Selection approaches from literature along with strengths and weaknesses of each.

Chapter-3: Rough Set Theory

This chapter will provide introduction of Rough Set theory along with its background, particular features and differences from other set theories. As well as discuss basic concepts of rough Set theory. Examples will also be provided by using very small sample datasets.

Chapter-4: Advance Concepts in Rough Set theory

This chapter will discuss some advance concepts like rough set based heuristics, rules, lemmas etc.

Chapter-5: Rough Set Theory Based Feature Selection Techniques

Rough set theory has been successfully used for feature selection techniques. In this chapter, we will present various feature selection techniques which use RST concepts.

Chapter-6: Unsupervised Feature Selection Using RST

Unsupervised feature selection information that could find feature subsets without given any class labels. In this section, we will discuss some of the unsupervised feature subset algorithms based on rough set theory.

Chapter-7: Critical Analysis of Feature Selection Algorithms

Critical review of each approach discussed. Critical review will include strengths and weaknesses of each. Special emphasis will be given on complexity analysis of each approach.

Chapter -8: Dominance based Rough Set Approach

Dominance-based rough set approach (DRSA) is an extension to the conventional rough set approach which supports the preference order using dominance principle where an item having higher value of attributes should belong to higher decision classes.

Chapter -9: Fuzzy-Rough Sets

Fuzzy rough sets were introduced as a fuzzy generalization of rough sets. In this chapter, we discuss general approach to the fuzzification of rough sets.

Chapter-10: Introduction to Classic Rough Set Based APIs library

This chapter will provide details explanation of the RST based API library (that will provided with the book) along with working example of each of the API function. This chapter will work as instruction manual for the library.

Chapter-11: Dominance Based Rough Set API library

This chapter will provide details explanation of the dominance based RST API along with working example of each of the API function.