Title :
Augmenting a classifier ensemble with automatically generated class level patterns for higher accuracy
Author :
Arthi Venkataraman
Author_Institution :
BOS-Botworks, Wipro Technologies, Bangalore, India
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.
Keywords :
"Context","Predictive models"
Conference_Titel :
Technologies and Applications of Artificial Intelligence (TAAI), 2015 Conference on
Electronic_ISBN :
2376-6824
DOI :
10.1109/TAAI.2015.7407105