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The KDD CUP '99 data set has been widely used for intrusion detection and pattern mining in the last decade or so. Umpteen number of experiments pertaining to classification have been conducted on it.Many researchers have dedicated their resources for analysing this data set. But it has yet to be analysed by using Ensemble methods of classification. This paper contains experimental results obtained after classifying 10 % of the KDD CUP '99 data set using ensemble methods like Bagging,Boosting and compares their performance with the standard J-48 classification algorithm.Weka experimenter has been used to classify the 494020 records using the aforementioned classifiers and the advantages of ensembling have been discussed in accordance with the obtained results..

Using Ensemble Methods for Improving Classification of the KDD CUP ’99 Data Set