Integrated Architecture and Feature Selection Algorithm for Radial Basis Neural Networks

Name: Integrated Architecture and Feature Selection Algorithm for Radial Basis Neural Networks
Brand: Biblioscholar
SKU: 9781288282388
Price: 369 CZK
Availability: InStock

Autor: Timothy D Flietstra

Jazyk:

Vazba: Brožovaná

Vydavatel: Biblioscholar

Dostupnost: Skladem u dodavatele

Odesíláme za 14-21 dnů

369 Kč

The research contribution of this thesis is the first known integrated architecture and feature sele...

Informace o knize

Autor

Timothy D Flietstra

Jazyk

Angličtina

Vazba

Kniha - Brožovaná

Vydáno

2012

Stránek

EAN

9781288282388

ISBN

9781288282388

Enbook ID

08240921

Vydavatel

Biblioscholar

Hmotnost

168

Rozměry

189 x 246 x 5

Kompletní popis

The research contribution of this thesis is the first known integrated architecture and feature selection algorithm for Radial Basis Neural Networks (RBNN's). The objective is to apply the network iteratively to determine the final architecture and feature set used to evaluate a problem. Additionally, this thesis compares three different classification techniques, Discriminant Analysis (DA), Feed-Forward Neural Networks (FFN) and RBNN's against several hard to solve problems. These problems were used to evaluate general classifier performance as well as the performance of the feature selection techniques. This thesis describes the classification techniques as well as the measures used to evaluate them. It next develops a new clustering technique used to determine the network architecture and the saliency measure used to select features for RBNN's. Next, the thesis applies these techniques to three general problems, Block-C, the University of Wisconsin Breast Cancer Data (UWBCD) and a noise corrupted version of Fisher's Iris problem. Finally, the conclusions and recommendations for future research are provided.

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Integrated Architecture and Feature Selection Algorithm for Radial Basis Neural Networks

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