COMPARATIVE STUDY OF CLASSIFICATION ALGORITHM FOR TEXT BASED CATEGORIZATION

Omkar Ardhapure, Gayatri Patil, Disha Udani, Kamlesh Jetha

Abstract: Text categorization is a process in data mining which assigns predefined categories to free-text documents using machine learning techniques. Any document in the form of text, image, music, etc. can be classified using some categorization techniques. It provides conceptual views of the collected documents and has important applications in the real world. Text based categorization is made use of for document classification with pattern recognition and machine learning. Advantages of a number of classification algorithms have been studied in this paper to classify documents. An example of these algorithms is: Naive Bayes algorithm, K-Nearest Neighbor, Decision Tree etc. This paper presents a comparative study of advantages and disadvantages of the above mentioned classification algorithm

Keywords: Data Mining, Text Mining, Text Categorization, Machine Learning, Pattern Analysis, Naive Bayes’, KNN, Decision Tree.

DOI: https://doi.org/10.15623/ijret.2016.0502037