EMPIRICAL EVALUATION OF MACHINE LEARNING ALGORITHMS FOR AUTOMATIC DOCUMENT CLASSIFICATION

Automatic document classification process is the important area of research in the field of Text Mining(TM). Text mining is the process of discovering the interesting pattern or knowledge from huge amount of data. The document classification process used in many domains. Here, to take the classifica...

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Bibliographic Details
Published in:International journal of advanced research in computer science 2017-09, Vol.8 (8), p.299-302
Main Author: Arivoli, P.V.
Format: Article
Language:English
Subjects:
Algorithms
Artificial intelligence
Automatic classification
Bayesian analysis
Classification
Data mining
Machine learning
Regression models
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Summary:Automatic document classification process is the important area of research in the field of Text Mining(TM). Text mining is the process of discovering the interesting pattern or knowledge from huge amount of data. The document classification process used in many domains. Here, to take the classification process is apply SMS spam classification. The bench marked dataset is used and the same data set is processed in various ML algorithms of Naïve Bayes, Support Vector Machine, Decision Tree and Logistic Regression model. In this paper evaluates the results of various machine learning algorithms for automatic document classification in SMS spam classification.
ISSN:0976-5697
0976-5697
DOI:10.26483/ijarcs.v8i8.4699