Text Classification for Student Data Set using Naive Bayes Classifier and KNN Classifier

International Journal of Computer Trends and Technology (IJCTT)          
© 2017 by IJCTT Journal
Volume-43 Number-1
Year of Publication : 2017
Authors : Rajeswari R.P, Kavitha Juliet, Dr.Aradhana
DOI :  10.14445/22312803/IJCTT-V43P103


Rajeswari R.P, Kavitha Juliet, Dr.Aradhana  "Text Classification for Student Data Set using Naive Bayes Classifier and KNN Classifier". International Journal of Computer Trends and Technology (IJCTT) V43(1):8-12, January 2017. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.

Abstract -
In this Information Era, Text documents with large features are available in plenty. Correct classification of this text documents into predefined set is a critical task. Text document classification is an emerging field in the area of text mining. Text classification is gorgeous because it eliminates the need of manually organizing documents based on their content and provides good accuracy. For Automated Text Classification a number of classifiers are available. In this paper, our focus is on text classification using Naïve Bayes classifier and K-Nearest Neighbour classifier and to emphasize on performance and accuracy of these classifiers using Rapid miner for Student Data Set.

[1].Bhumika, Prof Sukhjit Singh Sehra, and Prof Anand Nayyar. "A review paper on algorithms used for text classification." International Journal of Application or Innovation in Engineering & Management 3.2 (2013): 90-99.
[2]. Korde, Vandana, and C. Namrata Mahender. "Text classification and classifiers: A survey." International Journal of Artificial Intelligence & Applications 3.2 (2012): 85.
[3].Ikonomakis, M., S. Kotsiantis, and V. Tampakas. "Text classification using machine learning techni ques." WSEAS transactions on computers 4.8 (2005): 966-974.
[4] Kamruzzaman, S. M., Farhana Haider, and Ahmed Ryadh Hasan. "Text classification using data mining." arXiv preprint arXiv:1009.4987 (2010).
[5] Joachims, Thorsten. "Text categorization with support vector machines: Learning with many relevant features." European conference on machine learning. Springer Berlin Heidelberg, 1998.
[6]. Menaka, S., and N. Radha. "Text classification using keyword extraction technique." International Journal of Advanced Research in Computer Science and Software Engineering 3.12 (2013).
[7] Williamson, Eric R., and Saurabh Chakravarty. "CS5604 Fall 2016 Classification Team Final Report." (2016).
[8] Dalal, Mita K., and Mukesh A. Zaveri. "Automatic text classification: a technical review." International Journal of Computer Applications 28.2 (2011): 37-40.
[9] Ting, S. L., W. H. Ip, and Albert HC Tsang. "Is Naive Bayes a good classifier for document classification?." International Journal of Software Engineering and Its Applications 5.3 (2011): 37-46.
[10] Mahesh Kini M , Saroja Devi H , Prashant G Desai, Niranjan Chiplunkar.” Text Mining Approach to Classify Technical Research Documents using Naïve Bayes” International Journal of Advanced Research in Computer and Communication Engineering Vol. 4, Issue 7, July 2015.
[11]. Gongde Guo, Hui Wang, David Bell, Yaxin Bi and Kieran Greer, “KNN Model-Based Approach in Classification”, Proc. ODBASE pp- 986 – 996, 2003.

Text Mining, Text Classification, Naïve Bayes Classifier, KNN Classifier.