Fuzzy Modeling and Genetic Algorithms for Data Mining and Exploration
Downloading requires a password.
The password is the last word found on page 267 of the book.
From the Back Cover
Fuzzy Modeling and Genetic Algorithms for Data Mining and Exploration is a handbook for analysts, engineers, and managers involved in developing data mining models in business and government. As youll discover, fuzzy systems are extraordinarily valuable tools for representing and manipulating all kinds of data, and genetic algorithms and evolutionary programming techniques drawn from biology provide the most effective means for designing and tuning these systems.
You dont 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.
Features:
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.
About the Author:
Earl Cox is the founder and president of Scianta Intelligence, a next-generation machine intelligence and knowledge exploration company. He is a futurist, author, management consultant, and educator dedicated to the epistemology of advanced intelligent systems, the redefinition of the machine mind, and the ways in which evolving and inter-connected virtual worlds affect the sociology of business and culture. He is a recognized expert in fuzzy logic and adaptive fuzzy systems and a pioneer in the integration of fuzzy neural systems with genetic algorithms and case-based reasoning.
Product Description:
Fuzzy Modeling and Genetic Algorithms for Data Mining and Exploration is a handbook for analysts, engineers, and managers involved in developing data mining models in business and government. As youll discover, fuzzy systems are extraordinarily valuable tools for representing and manipulating all kinds of data, and genetic algorithms and evolutionary programming techniques drawn from biology provide the most effective means for designing and tuning these systems.
You dont 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.
Product Details
• Paperback: 500 pages
• Publisher: Morgan Kaufmann; 1st edition (Jan, 2005)
• ISBN: 0121942759
|
