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Anomaly Intrusion Detection Using Incremental Learning of an Infinite Mixture Model with Feature Selection
[chapter]
2013
Lecture Notes in Computer Science
We propose an incremental nonparametric Bayesian approach for clustering. Our approach is based on a Dirichlet process mixture of generalized Dirichlet (GD) distributions. Unlike classic clustering approaches, our model does not require the number of clusters to be pre-defined. Moreover, an unsupervised feature selection scheme is integrated into the proposed nonparametric framework to improve clustering performance. By learning the proposed model using an incremental variational framework, the
doi:10.1007/978-3-642-41299-8_35
fatcat:fzjku6yiufh63a2r4pu2pk2s4q