Information Fusion(Ensemble System)in Data Warehousing and Data Mining

Language: English

Published by LAP LAMBERT Academic Publishing Okt 2013, 2013

3659395870 / 9783659395871

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This item is printed on demand - Print on Demand Titel. Neuware -Information fusion is becoming a major need in Data Mining. Typical applications of these techniques include data modeling (ensemble methods). The behavior of various classification algorithms differs based on accuracy and computational complexity. For some algorithms there may be a significant variation in the performance when some parameters are varied. In this research the behavior of the modified AdaBoost algorithm with NN as a base classifier and as a preprocessing step feature selection combined with the evaluation schemas (like subset evaluation, consistency based, correlation based, filter approach, wrapper approach etc.) are applied by varying the number of parameters. Predictive accuracy is substantially improved when combining multiple predictors. A novel idea of an Ensemble System applying Boosting to Neural Networks for High Dimensional Datasets. The method uses Genetic Algorithms (to select relevant features) for essential feature selection with various Evaluation Schemes. As Genetic Algorithms deal well with large solution spaces, tuning it to adjust as per the requirements of the ensemble, we can get optimum feature selection. Finally Boosting algorithm that finisheOmniScriptum SRL, Str. Armeneasca 28/1, office 1, 2012 Chisinau 200 pp. Englisch.

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Title
Information Fusion(Ensemble System)in Data Warehousing and Data Mining
Author
Amit Ganatra
Publisher
LAP LAMBERT Academic Publishing Okt 2013
Publication year
2013
Condition
Neu
Binding
Taschenbuch
Language
English
ISBN 10
3659395870
ISBN 13
9783659395871
Item weight
316 grams
Dimensions
220x150x13 mm

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