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Data Mining with Computational Intelligence
Author
Title
Data Mining with Computational Intelligence [electronic resource] / by Lipo Wang, Xiuju Fu.
ISBN
9783540288039
Publication
Berlin, Heidelberg : Springer Berlin Heidelberg, 2005.
Physical Description
1 online resource (XI, 276 p).
Local Notes
Access is available to the Yale community.
Access and use
Access restricted by licensing agreement.
Summary
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.
Variant and related titles
Springer ENIN.
Other formats
Printed edition:
Printed edition:
Printed edition:
Format
Books / Online
Language
English
Added to Catalog
June 17, 2019
Series
Advanced Information and Knowledge Processing,
Contents
MLP Neural Networks for Time-Series Prediction and Classification
Fuzzy Neural Networks for Bioinformatics
An Improved RBF Neural Network Classifier
Attribute Importance Ranking for Data Dimensionality Reduction
Genetic Algorithms for Class-Dependent Feature Selection
Rule Extraction from RBF Neural Networks
A Hybrid Neural Network For Protein Secondary Structure Prediction
Support Vector Machines for Prediction
Rule Extraction from Support Vector Machines.
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