This book bridges the gap between daily practice of cluster analysis and computer-assisted (knowledge-based) diagnostic support in cluster analysis. It incorporates hands-on experience through the EDAPLUS software package that goes with the book. Coverage includes a detailed explanation of the concept of fuzzy sets and fuzzy logic in cluster analysis; numerous examples of artificial and real data; and a detailed case study of a sonar sound signal cluster analysis. This work is intended for final year undergraduate and MSc students in departments of electrical engineering and computer science studying pattern recognition and/or knowledge-based systems.
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Bridging the gap between exploratory data analysis and computer-assisted (knowledge-based) reasoning, this book offers a comprehensive introduction to the methodology of cluster analysis. Covers the problems related to cluster tendency and cluster validity. Includes a detailed explanation of the concept of fuzzy sets and fuzzy logic in cluster analysis. Provides a diskette with the software package EDAPLUS, with the algorithms presented in the text and the computer-assisted reasoning as discussed. For researchers in the field of application oriented approaches in industrial pattern recognition and applied AI- software engineering.
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