Fusion Methods for Unsupervised Learning Ensembles

Language: English

Published by Springer Spektrum, 2010

3642162045 / 9783642162046

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Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH

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Druck auf Anfrage Neuware - Printed after ordering - The application of a 'committee of experts' or ensemble learning to artificial neural networksthat apply unsupervised learning techniques is widely considered to enhance the effectivenessof such networks greatly.This book examines the potential of the ensemble meta-algorithm by describing and testing atechnique based on the combination of ensembles and statistical PCA that is able to determinethe presence of outliers in high-dimensional data sets and to minimize outlier effects in the final results.Its central contribution concerns an algorithm for the ensemble fusion of topology-preservingmaps, referred to as Weighted Voting Superposition (WeVoS), which has been devised to improve data exploration by 2-D visualization over multi-dimensional data sets. This generic algorithm is applied in combination with several other models taken from the family of topology preserving maps, such as the SOM, ViSOM, SIM and Max-SIM. A range of quality measures for topology preserving maps that are proposed in the literature are used to validate and compare WeVoS with other algorithms.The experimental results demonstrate that, in the majority of cases, the WeVoS algorithmoutperforms earlier map-fusion methods and the simpler versions of the algorithm with whichit is compared. All the algorithms are tested in different artificial data sets and in several of the most common machine-learning data sets in order to corroborate their theoretical properties. Moreover, a real-life case-study taken from the food industry demonstrates the practical benefits of their application to more complex problems.

Seller Inventory # 9783642162046

Title
Fusion Methods for Unsupervised Learning Ensembles
Author
Bruno Baruque
Publisher
Springer Spektrum
Publication year
2010
Condition
Neu
Binding
Buch
Language
English
ISBN 10
3642162045
ISBN 13
9783642162046
Item weight
442 grams
Dimensions
241x160x15 mm

AHA-BUCH GmbH

Einbeck, Germany

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