Text Classification Using Ensemble of Non-Linear Support Vector Machines
Sheelesh Kumar Sharma1, Navel Kishor Sharma2
1Dr Sheelesh Kumar Sharma, Professor (Comp. Sc.), IMS Ghaziabad, India.
2Mr Navel Kishor Sharma, Associate Dean, Academic City College Ghana.
Manuscript received on 02 August 2019 | Revised Manuscript received on 05 August 2019 | Manuscript published on 30 August 2019 | PP: 3169-3174 | Volume-8 Issue-10, August 2019 | Retrieval Number: J95200881019/19©BEIESP | DOI: 10.35940/ijitee.J9520.0881019
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: With the advent of digital era, billions of the documents generate every day that need to be managed, processed and classified. Enormous size of text data is available on world wide web and other sources. As a first step of managing this mammoth data is the classification of available documents in right categories. Supervised machine learning approaches try to solve the problem of document classification but working on large data sets of heterogeneous classes is a big challenge. Automatic tagging and classification of the text document is a useful task due to its many potential applications such as classifying emails into spam or non-spam categories, news articles into political, entertainment, stock market, sports news, etc. The paper proposes a novel approach for classifying the text into known classes using an ensemble of refined Support Vector Machines. The advantage of proposed technique is that it can considerably reduce the size of the training data by adopting dimensionality reduction as pre-training step. The proposed technique has been used on three bench-marked data sets namely CMU Dataset, 20 Newsgroups Dataset, and Classic Dataset. Experimental results show that proposed approach is more accurate and efficient as compared to other state-of-the-art methods.
Keywords: Text Classification, Support Vector Machine, Non-Linear Ensemble, Machine Learning, Natural Language Processing.
Scope of the Article: Classification