Improving K2 Algorithm by Single Link Clustering For Bayesian Network Structural Learning

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Provided by: International Association of Computer Science and Information Technology(IACSIT)
Topic: Networking
Format: PDF
A Bayesian Network (BN) is an appropriate tool to work with the uncertainty that is typical of real-life applications. Basically, a BN provides an effective graphical language for factoring joint probability distributions. Two important methods of learning bayesian are parametric learning and structural learning. Finding bayesian network structure is a NP-hard problem. In this paper, the authors introduced structural learning in bayesian network and key learning algorithms, like Hill Climbing and K2 and briefly. As a second step, they presented a new structural learning method using composite of k2 search algorithm and single link clustering method.
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