A Survey of Various Machine Learning Techniques for Text Classification
|International Journal of Engineering Trends and Technology (IJETT)|
|© 2014 by IJETT Journal|
|Year of Publication : 2014|
|Authors : Gaurav S. Chavan , Sagar Manjare , Parikshit Hegde , Amruta Sankhe
Gaurav S. Chavan , Sagar Manjare , Parikshit Hegde , Amruta Sankhe. "A Survey of Various Machine Learning Techniques for Text Classification", International Journal of Engineering Trends and Technology (IJETT), V15(6),288-292 Sep 2014. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group
Sentiments are expressions of one’s words in a sentence. Hence understanding the meaning of text in the sentence is of utmost importance to people of various fields like customer reviews in companies, movie reviews in movies, etc. It may involve huge text data to analyze and it becomes totally unviable for manually understanding the meaning of sentences. Classifier algorithms should be used to classify the various meaning of the sentences. By using pre-defined data to train our classifier and three different algorithms namely Naive Bayes, Support Vector Machines, Decision Trees, we can simplify the task of text classification. Using relevant results and examples we will prove that SVM is one of the better algorithms in providing higher accuracy over the other two algorithms i.e. Naive Bayes and Decision Tree.
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Text Classification, Sentiment Analysis, Algorithms, Naive Bayes, SVM, Decision Tree