Neural Processing Letters, ( ISI ), Volume (35), No (1), Year (2012-1) , Pages (61-80)

Title : ( Making Diversity Enhancement Based on Multiple Classifier System by Weight Tuning )

Authors: Mohammad Mehdi Salkhordeh haghighi , Abedin Vahedian Mazloum , Hadi Sadoghi Yazdi ,

Citation: BibTeX | EndNote

This article presents a new method to construct multiple classifier system by making diverse base classifiers using weight tuning. In the method presented, base classifiers are multilayer perceptions which creates diverse base classifiers using a three-step proce- dure. In the first step, base classifiers are trained for acceptable accuracy. In the second step, a weight tuning process tunes their weights such that each one can distinguish one class of input data from the others with highest possible accuracy. An evolutionary method is used to optimize efficiency of each base classifier to distinguish one class of input data in this step. In the third step, a new method combines the results of the base classifiers. As diversity is measured and monitored throughout the entire procedure, it is measured using a confusion matrix. Superiority of the proposed method is discussed using several known classifier fusion methods and known benchmark datasets.

Keywords

Combining classifiers · Classifier fusion · Classifier diversity · Multiple classifier system
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@article{paperid:1024906,
author = {Salkhordeh Haghighi, Mohammad Mehdi and Vahedian Mazloum, Abedin and Sadoghi Yazdi, Hadi},
title = {Making Diversity Enhancement Based on Multiple Classifier System by Weight Tuning},
journal = {Neural Processing Letters},
year = {2012},
volume = {35},
number = {1},
month = {January},
issn = {1370-4621},
pages = {61--80},
numpages = {19},
keywords = {Combining classifiers · Classifier fusion · Classifier diversity · Multiple classifier system diversity},
}

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%0 Journal Article
%T Making Diversity Enhancement Based on Multiple Classifier System by Weight Tuning
%A Salkhordeh Haghighi, Mohammad Mehdi
%A Vahedian Mazloum, Abedin
%A Sadoghi Yazdi, Hadi
%J Neural Processing Letters
%@ 1370-4621
%D 2012

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