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.
Author(s): Lipo Wang
Edition: 1
Year: 2005
Language: English
Pages: 280
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
