Computational Intelligence and Feature

This book provides readers with the background and fundamental ideas behind Feature Selection (FS), with an emphasis on techniques based on rough and fuzzy sets. For readers who are less familiar with the subject, the book begins with an introduction to fuzzy set theory and fuzzy-rough set theory. Next it provides a critical review of FS methods with an emphasis on their current limitations, program files used to implement major algorithms, and associated areas of FS, including rule induction and clustering methods using hybridization of fuzzy and rough set theories.

Richard Jensen, PhD, is a Lecturer with the Department of Computer Science at Aberystwyth University, United Kingdom. Dr. Jensen has published extensively in the subject area of Feature Selection. Additionally, he has taught master's courses in engineering knowledge-based systems and served as supervisor for many student projects on Feature Selection, fuzzy-rough systems modeling, and swarm intelligence at both the University of Edinburgh, Scotland, and the University of Wales.

Qiang Shen, PhD, is Professor and Director of Research with the Department of Computer Science at Aberystwyth University, and an Honorary Fellow at the University of Edinburgh. Dr. Shen's research interests include artificial and computational intelligence. He is an associate editor and editorial board member of several world-leading journals and has been a chair or cochair of many national and international conferences in his research area.

Preface
The Importance of Feature Selection
Knowledge Discovery
Feature Selection
The Task
The Benefits
Rough Sets
Applications
Structure
Set Theory
Classical Set Theory
Definition
Subsets
Operators
Fuzzy Set Theory
Definition
Operators
Simple Example
Fuzzy Relations and Composition
Approximate Reasoning
Linguistic Hedges
Fuzzy Sets and Probability
Rough Set Theory
Information and Decision Systems
Indiscernibility
Lower and Upper Approximations
Positive, Negative, and Boundary Regions
Feature Dependency and Significance
Reducts
Discernibility Matrix
Fuzzy-Rough Set Theory
Fuzzy Equivalence Classes
Fuzzy-Rough Sets
Rough-Fuzzy Sets
Fuzzy-Rough Hybrids
Summary
Classification Methods
Crisp Approaches
Rule Inducers
Decision Trees
Clustering
Naive Bayes
Inductive Logic Programming
Fuzzy Approaches
Lozowski's Method
Subsethood-Based Methods
Fuzzy Decision Trees
Evolutionary Approaches
Rulebase Optimization
Fuzzy Interpolation
Fuzzy Rule Optimization
Summary
Dimensionality Reduction
Transformation-Based Reduction
Linear Methods
Nonlinear Methods
Selection-Based Reduction
Filter Methods
Wrapper Methods
Genetic Approaches
Simulated Annealing Based Feature Selection
Summary
Rough Set Based Approaches to Feature Selection
Rough Set Attribute Reduction
Additional Search Strategies
Proof of QuickReduct Monotonicity
RSAR Optimizations
Implementation Goals
Implementational Optimizations
Discernibility Matrix Based Approaches
Johnson Reducer
Compressibility Algorithm
Reduction with Variable Precision Rough Sets
Dynamic Reducts
Relative Dependency Method
Tolerance-Based Method
Similarity Measures
Approximations and Dependency
Combined Heuristic Method
Alternative Approaches
Comparison of Crisp Approaches
Dependency Degree Based Approaches
Discernibility Matrix Based Approaches
Summary
Applications I: USE OF RSAR
Medical Image Classification
Problem Case
Neural Network Modeling
Results
Text Categorization
Problem Case
Metrics
Datasets Used
Dimensionality Reduction
Information Content of Rough Set Reducts
Comparative Study of TC Methodologies
Efficiency Considerations of RSAR
Generalization
Algae Estimation
Problem Case
Results
Other Applications
Prediction of Business Failure
Financial Investment
Bioinformatics and Medicine
Fault Diagnosis
Spacial and Meteorological Pattern Classification
Music and Acoustics
Summary
Rough and Fuzzy Hybridization
Introduction
Theoretical Hybridization
Supervised Learning and Information Retrieval
Feature Selec
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Computational Intelligence and Feature Selection Rough and Fuzzy Approaches

Summary

Author Biography

Table of Contents

Supplemental Materials