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Associative classification (AC) integrates the task of mining association rules with the classification task to increase the efficiency of the classification process. AC algorithms produce accurate classification and generate easy to understand rules. However, AC algorithms suffer from two drawbacks: the large number of classification rules, and using different pruning methods that may remove vital...
Naive Bayes classifier has been extensively applied in various domains in the past few decades due to its simple structure and remarkable predictive performance. However, it is based on a strong assumption which confines its usage for many real-world applications; conditional independence of attributes given class information. In this paper, we propose mixture of latent multinomial naive Bayes (MLMNB)...
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