Intrusion Detection System Using Bagging with Partial Decision TreeBase Classifier

Author:

Gaikwad D.P.,Thool Ravindra C.

Publisher

Elsevier BV

Subject

General Engineering

Reference10 articles.

1. Eric Bauer and Ron Kohavi. An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Variants. Machine Learning, Kluwer Academic Publishers, Boston. Manufactured in The Netherlands 1998.

2. An Experimental Comparison of Three Methods for Constructing Ensembles of Decision Trees: Bagging, Boosting, and Randomization;Dietterich,1999

3. Shrinivasu and P.S. Avadhani. Genetic Algorithm based Weight Extraction Algorithm for Artificial Neural Network Classifier in intrusion Detection. In Procedia Engineering 38 (2012) 144-153, Published by Elsevier Ltd.,2012.

4. Li Hanguang, Ni Yu. Intrusion Detection Technology Research Based on Apriori Algorithm. In International Conference on Applied Physics and Industrial Engineering-2012.

5. Gisung Kim, Seungmin Lee and Sehun Kim. A novel hybrid intrusion detection method integrating anomaly detection with misuse detection. In journal of Expert Systems with Applications, Published by Elsevier-2014.

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