Artificial Intelligence and Signal Processing (AISP), 2012 16th CSI International Symposium on , 2012-05-02

Title : ( Constraint excluded classifier )

Authors: Hassan Abbassi , Reza Monsefi , Hadi Sadoghi Yazdi ,

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Abstract

Linear classifiers have the generalization property while lacking the power of classifying complex patterns. A simple and effective idea is to somehow exclude the complexity of the data such that it can be classified using a linear classifier. In this paper a new classifier system called “Constraint Excluded Classifier” is proposed that classifies most of the input patterns using a simple, e.g., a linear classifier. The classification is composed of an iterative three step loop. In the “Construction” step, several sub-classifiers are constructed which are responsible for linearly classifying parts of input patterns. Sub-classifiers are merged together in the “Fusion” step. The “Evaluation” step tests and fine tunes the construction of sub-classifiers. The comparison of the new classifier with famous classifiers is also presented.

Keywords

, Linear Classification, Multiple Classifier System, Constraint Classification, Classifier Boosting
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@inproceedings{paperid:1042108,
author = {Abbassi, Hassan and Monsefi, Reza and Sadoghi Yazdi, Hadi},
title = {Constraint excluded classifier},
booktitle = {Artificial Intelligence and Signal Processing (AISP), 2012 16th CSI International Symposium on},
year = {2012},
keywords = {Linear Classification; Multiple Classifier System; Constraint Classification; Classifier Boosting},
}

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%0 Conference Proceedings
%T Constraint excluded classifier
%A Abbassi, Hassan
%A Monsefi, Reza
%A Sadoghi Yazdi, Hadi
%J Artificial Intelligence and Signal Processing (AISP), 2012 16th CSI International Symposium on
%D 2012

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