Data Mining with Computational Intelligence (Advanced Information and Knowledge Processing)

Finding information hidden in data is as theoretically difficult as it is practically important. With the objective of discovering unknown patterns from data, the methodologies of data mining were derived from statistics, machine learning, and artificial intelligence, and are being used successfully in application areas such as bioinformatics, banking, retail, and many others. Wang and Fu present in detail the state of the art on how to utilize fuzzy neural networks, multilayer perceptron neural networks, radial basis function neural networks, genetic algorithms, and support vector machines in such applications. They focus on three main data mining tasks: data dimensionality reduction, classification, and rule extraction. The book is targeted at researchers in both academia and industry, while graduate students and developers of data mining systems will also profit from the detailed algorithmic descriptions. Cover......Page 1 Data Mining with Computational Intelligence......Page 3 Advanced Information and Knowledge Processing......Page 2 ISBN-10 3540245227......Page 4 Preface......Page 5 Contents......Page 7 1 Introduction......Page 12 2 MLP Neural Networks for Time-Series Prediction and Classification......Page 35 3 Fuzzy Neural Networks for Bioinformatics......Page 54 4 An Improved RBF Neural Network Classifier......Page 105 5 Attribute Importance Ranking for Data Dimensionality Reduction......Page 125 6 Genetic Algorithms for Class-Dependent Feature Selection......Page 152 7 Rule Extraction from RBF Neural Networks......Page 164 8 A Hybrid Neural Network For Protein Secondary Structure Prediction......Page 195 9 Support Vector Machines for Prediction......Page 230 10 Rule Extraction from Support Vector Machines......Page 242 glossary names......Page 254 A Rules extracted for the Iris data set......Page 256 References......Page 258 Index......Page 279

Finding information hidden in data is as theoretically difficult as it is practically important. With the objective of discovering unknown patterns from data, the methodologies of data mining were derived from statistics, machine learning, and artificial intelligence, and are being used successfully in application areas such as bioinformatics, banking, retail, and many others.

Wang and Fu present in detail the state of the art on how to utilize fuzzy neural networks, multilayer perceptron neural networks, radial basis function neural networks, genetic algorithms, and support vector machines in such applications. They focus on three main data mining tasks: data dimensionality reduction, classification, and rule extraction.

The book is targeted at researchers in both academia and industry, while graduate students and developers of data mining systems will also profit from the detailed algorithmic descriptions.

"Lipo Wang and Xiuju Fu present in detail the state of the art on how to utilize fuzzy neural networks, multilayer perceptron neural networks, radial basis function neural networks, genetic algorithms, and support vector machines in such applications. They focus on three main data mining tasks: data dimensionality reduction, classification, and rule extraction." "The book is targeted at researchers in both academia and industry, while graduate students and developers of data mining systems will also profit from the detailed algorithmic descriptions."--Résumé de l'éditeur "Lipo Wang and Xiuju Fu present in detail the state of the art on how to utilize fuzzy neural networks, multilayer perceptron neural networks, radial basis function neural networks, genetic algorithms, and support vector machines in such applications. They focus on three main data mining tasks: data dimensionality reduction, classification, and rule extraction." "The book is targeted at researchers in both academia and industry, while graduate students and developers of data mining systems will also profit from the detailed algorithmic descriptions."--BOOK JACKET