The first book to cover data mining from a computational intelligence perspective, Fuzzy Modeling Tools for Data Mining and Knowledge Discovery. focuses on how techniques such as fuzzy rule induction, genetic algorithms, and intelligent agents can help you discern patterns buried deep within your data. Cox begins by examining the nature of knowledge discovery and why a "fuzzy" approach can be especially effective. From there, he reviews specific fuzzy data mining techniques with an eye to their strengths and weaknesses, providing all the necessary technical background and developing a comprehensive methodology you can follow, step by step, to meet your organization's needs. This is the first book to cover data mining from a computational intelligence viewpoint. Its focus is data mining using a blend of computational intelligence techniques--fuzzy rule induction, genetic algorithms, intelligent agents--to create actual models of the behaviors or patterns buried deep in a wide variety of data sources. Concentrating on real-world problems, the book uses actual case studies, develops a comprehensive methodology, and provides all of the necessary background in the technologies. Cox examines the nature of knowledge discovery, and reviews and analyzes various data mining approaches with an eye to their strengths and weaknesses. The data mining process uses a Windows-based knowledge discovery system (Metus/KDS), as well as Java and C/C++ code.