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Naive Bayes Classifier
Naive Bayes Classifier
Publications: 540| Citation Count: 8,568
Stemming Variations: naive Bayes classifiers
Cumulative Annual
    • Naive Bayes classifier is a simple and effective classification method, but its attribute independence assumption makes it unable to express the dependence among attributes, and affects its classification performance. On the basis of analyzing the classification principle of Bayesian classification model and a variant of Bayes theorem, a new classification model based on Bayes theorem, DLBAN (double-level Bayesian network augmented naive Bayes), which adds the dependence among attributes by selecting the key attributes, is proposed...

    SHI Hong-Bo, et al. A Restricted Double-Level Bayesian Classification Model

    • Naive-Bayes classifier is a popular technique of classification in machine learning. Improving the accuracy of naive-Bayes classifier will be significant as it has great importance in classification using numerical attributes...

    B. Chandra, et al. Robust Approach for Estimating Probabilities in Naive-Bayes Classifier

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Publications (540)

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