A Regularized Linear Classifier for Effective Text Classification

  • Sharad Nandanwar
  • M. Narasimha Murty
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7664)


In document community support vector machines and naïve bayes classifier are known for their simplistic yet excellent performance. Normally the feature subsets used by these two approaches complement each other, however a little has been done to combine them. The essence of this paper is a linear classifier, very similar to these two. We propose a novel way of combining these two approaches, which synthesizes best of them into a hybrid model. We evaluate the proposed approach using 20ng dataset, and compare it with its counterparts. The efficacy of our results strongly corroborate the effectiveness of our approach.


Support Vector Machine Naïve Bayes Classifier Regularization 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Sharad Nandanwar
    • 1
  • M. Narasimha Murty
    • 1
  1. 1.Department of Computer Science and AutomationIndian Institute of ScienceBangaloreIndia

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