You don’t need a background in fuzzy modeling or genetic algorithms to benefit, for this book provides it, along with detailed instruction in methods that you can immediately put to work in your own projects. The author provides many diverse examples and also an extended example in which evolutionary strategies are used to create a complex scheduling system.

• Written to provide analysts, engineers, and managers with the background and specific instruction needed to develop and implement more effective data mining systems
• Helps you to understand the trade-offs implicit in various models and model architectures
• Provides extensive coverage of fuzzy SQL querying, fuzzy clustering, and fuzzy rule induction
• Lays out a roadmap for exploring data, selecting model system measures, organizing adaptive feedback loops, selecting a model configuration, implementing a working model, and validating the final model
• In an extended example, applies evolutionary programming techniques to solve a complicated scheduling problem
• Presents examples in C, C++, Java, and easy-to-understand pseudo-code
• Extensive online component, including sample code and a complete data mining workbench