• N.G.Sree Devi
• M.Jeyanthi

Data Mining is becoming one of the leading techniques applicable in a variety of area. Classification is a supervised learning approach of data mining and it is used to classify huge data. The dataset have been chosen from UCI Machine Learning Repository. Weka is a powerful machine learning tool that contains many built in algorithms to extract knowledge. In this paper we analyse the classification algorithms such as Naïve Bayes , K-Star, Random Forest, One-R. The multiple parameters taken into considerations for analytical purpose are Accuracy, True Positive Rate, False Positive Rate, Precision, Recall, F-Measure. Finally we observed the performance of the classification algorithm for the UCI Machine Learning data set.

Naïve Bayes, K-Star, Random Forest, One-R, Data Mining

"Comparative Analysis Of Classification Algorithm Using Machine Learning Technique", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 2, page no.485-489, February-2019, Available :http://www.jetir.org/papers/JETIRAB06084.pdf

"Comparative Analysis Of Classification Algorithm Using Machine Learning Technique", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 2, page no. pp485-489, February-2019, Available at : http://www.jetir.org/papers/JETIRAB06084.pdf