Adjusted Probability Naive Bayesian InductionGeo rey
نویسنده
چکیده
Naive Bayesian classiiers utilise a simple mathematical model for induction. While it is known that the assumptions on which this model is based are frequently violated, the predictive accuracy obtained in discriminate classiication tasks is surprisingly competitive in comparison to more complex induction techniques. Adjusted probability naive Bayesian induction adds a simple extension to the naive Bayesian clas-siier. A numeric weight is inferred for each class. During discriminate classiication, the naive Bayesian probability of a class is multiplied by its weight to obtain an adjusted value. The use of this adjusted value in place of the naive Bayesian probability is shown to signiicantly improve predictive accuracy.
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Adjusted Probability Naive Bayesian
Naive Bayesian classiiers utilise a simple mathematical model for induction. While it is known that the assumptions on which this model is based are frequently violated, the predictive accuracy obtained in discriminate classiication tasks is surprisingly competitive in comparison to more complex induction techniques. Adjusted probability naive Bayesian induction adds a simple extension to the n...
متن کاملAdjusted Probability Naive Bayesian Induction
Naive Bayesian classi ers utilise a simple mathematical model for induction. While it is known that the assumptions on which this model is based are frequently violated, the predictive accuracy obtained in discriminate classi cation tasks is surprisingly competitive in comparison to more complex induction techniques. Adjusted probability naive Bayesian induction adds a simple extension to the n...
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