• Aman Chauhan
• A.J. Singh

In present scenario the rise of digital technology, the availability of raw data over the network has increased awfully and this data is continuously increasing day by day. The data which is generated by these technologies needs to be processed and analyzed in some efficient ways that the information thus extracted can help serving for better results. Data Mining is one of the hot topics in which researchers and academician putting an interest. Data mining offers various techniques and methods that may be used to predict the future trends and patterns in available data. There are various number of techniques which can be used to predict the class in which the particular data falls .Classification is used for analyzing the data and the comparison has been done over the set of parameters like correctly and incorrectly classified instances .The unbounded size and imbalance nature of data creates difficulty in Classification so there are ensemble methods to solve these problems. Problems of over-fitting and bias are also solved with Ensemble Learning Methods. This research focuses on analyzing the behavior of Ensemble Learning Methods (Bagging, Boosting) with the help of five base classifiers, i.e. Naïve Bayes, Decision Table, J48, OneR and Decision Stump over the varying size data. WEKA tool has been used for the experimental purpose and the parameters that helped in evaluating the performance are accuracy, error rate, precision and recall.

DATA MINING, CLASSIFICATION, WEKA TOOL, ENSEMBLE LEARNING METHOD, BAGGING, BOOSTING

"Performance Analysis of Ensemble Learning Methods with Base Classifiers for Data Mining ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.835-843, June 2019, Available :http://www.jetir.org/papers/JETIR1906G28.pdf

"Performance Analysis of Ensemble Learning Methods with Base Classifiers for Data Mining ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp835-843, June 2019, Available at : http://www.jetir.org/papers/JETIR1906G28.pdf