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Authors
Affiliations
1 Department of CSE, K.S Institute of Technology, Bengaluru, IN
Source
International Journal of Engineering Research, Vol 5, No SP 4 (2016), Pagination: 822-824
Abstract
The paper uses supervised machine learning and content-based document classification of textual documents that are confined to four educational departments-Civil, Computer Science, Mechanical and Electrical Engineering by using TF-IDF algorithm along with Natural Language Processing for feature selection and ID3 algorithm as a classifier. The results show 80% accuracy.
Keywords
Supervised Machine Learning, Natural Language Processing, TF-IDF, Iterative Dichotomiser 3.
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