conference-paper

Augmenting a classifier ensemble with automatically generated class level patterns for higher accuracy

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Abstract

Different types of classifiers were investigated in the context of classification of problem tickets in the Enterprise domain. There were still challenges in building an accurate classifier post data cleaning and other accuracy improving pre-processing techniques. Creating an ensemble of classifiers gave better accuracy than individual classifiers. The maximum accuracy was got by enhancing the ensemble with an additional automatically generated domain specific class wise keyword list. Use of this system gave us greater than 4 percent improvement over the techniques of just using the ensemble classifier. A further improvement in accuracy was obtained when a semi-supervised approach was followed where the automatically generated class level keys are further reviewed by domain team before usage.

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Publication details

DOI
10.1109/taai.2015.7407105
OpenAlex
W2548532431
Document type
conference-paper
Language
EN
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