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Currently, web spamming is a serious problem for search engines. It not only degrades the quality of search results by intentionally boosting undesirable web pages to users, but also causes the search engine to waste a significant amount of computational and storage resources in manipulating useless information. In this paper, we present a novel ensemble classifier for web spam detection which combines...
MBBNTree algorithm, which integrates the advantage of Markov blanket Bayesian networks (MBBN) and decision tree, would behave better performance than other Bayesian networks for classification. But the available training samples with actual classes are not enough for building MBBNTree classifier in practice. Active learning aims at reducing the number of training examples to be labeled by automatically...
For the purpose of improving the predictive accuracy and interpretability of telecom customer retention prediction model, MBBCTree Algorithm, which integrates the advantage of Markov blanket Bayesian networks (MBBC) and decision tree, is proposed in this paper to predict customers' lifetime. MBBCTree classifier uses a tree structure to split the instance space into sub-spaces and generates one MBBC...
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