Multi-Class Text Classification with KNN Machine Learning Techniques

K Gayathri, A Marimutha

Abstract


Multi-label text classification deals with problems in which each document is associated with a subset of categories. The increasing availability of digital documents in the last decade has prompted the development of machine learning techniques to automatically classify and organize text documents. This article will focus on the feature selection for reducing the dimensionality of the vectors. Further training the classifier by K-nearest neighbor algorithms the predication can be made according to the category distribution among these K-nearest neighbors. Experimental results show that the methods are favorable in terms of their effectiveness and efficiency with the precision.

Keywords


Text classification, Multi-lable,TF/IDF, KNN.

References


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