An Analysis of Instance Selection Algorithms using Support Vector Machine for Text Classification
نویسنده
چکیده
Automatic text classification is a popular research topic in text mining. Automatic text classification is an eminent field of research in text mining, which is tries to automatically classify the text documents into pre-specified categories. Text mining involves several pre-processing and classification techniques. In this paper, we have analysed several feature selection methods with support vector machine for text classification. Several instance selection methods analysed with different aspects such as accuracy, processing time, reduction rate and selected support vectors. This analysis is mainly focused to techtc-100 dataset with several feature selection strategies. Support Vector Oriented Instance Selection is shown better efficiency in all aspects. This study is very useful to novice text mining researchers.
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