• Manuja Sharma
• Dr. K.L. Bansal

With the advent of technology, the amount of raw data which is available over the network is exploding day by day. It becomes extremely necessary to analyze this data and extract every possible information from it which helps in serving some or the other purpose. The way this huge amount of data is handled, analyzed and processed, this has become an interesting and fast growing area for research. Data mining offers various techniques and methods that may be used to predict the future trends and patterns in available data. There are number of techniques which can be used to predict the class in which the particular data falls. This research focuses on comparative analysis of various classification techniques, such as Naïve Bayes, Bayes Net, Random Forest, J48, Decision Table and lBK, which are used to predict the category of data. WEKA tool has been used to practically implement these classification techniques and the comparison has been done over the set of parameters like correctly and incorrectly classified instances, errors, kappa statistics, sensitivity, accuracy, specificity etc.

Data Mining, Classification, Naïve Bayes, Bayes Net, Random Forest, J48, Decision Table, lBK, WEKA Tool.

"A COMPARATIVE STUDY OF CLASSIFICATION TECHNIQUES BY UTILIZING WEKA TOOL", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 12, page no.240-247, December-2018, Available :http://www.jetir.org/papers/JETIR1812131.pdf

"A COMPARATIVE STUDY OF CLASSIFICATION TECHNIQUES BY UTILIZING WEKA TOOL", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 12, page no. pp240-247, December-2018, Available at : http://www.jetir.org/papers/JETIR1812131.pdf