Adjusted Probability Naive Bayesian Induction
نویسندگان
چکیده
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 naive Bayesian classi er. A numeric weight is inferred for each class. During discriminate classi cation, 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 signi cantly improve predictive accuracy.
منابع مشابه
Adjusted Probability Naive Bayesian InductionGeo rey
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
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 کاملEstimating Continuous Distributions in Bayesian Classifiers
When modeling a probability distribution with a Bayesian network, we are faced with the problem of how to handle continuous vari ables. Most previous work has either solved the problem by discretizing, or assumed that the data are generated by a single Gaussian. In this paper we abandon the normality as sumption and instead use statistical methods for nonparametric density estimation. For a n...
متن کاملA Validation Test Naive Bayesian Classification Algorithm and Probit Regression as Prediction Models for Managerial Overconfidence in Iran's Capital Market
Corporate directors are influenced by overconfidence, which is one of the personality traits of individuals; it may take irrational decisions that will have a significant impact on the company's performance in the long run. The purpose of this paper is to validate and compare the Naive Bayesian Classification algorithm and probit regression in the prediction of Management's overconfident at pre...
متن کاملTractable Average-Case Analysis of Naive Bayesian Classifiers
In this paper we present an average-case analysis of the naive Bayesian classiier, a simple induction algorithm that performs well in many domains. Our analysis assumes a monotonèM of N' target concept and training data that consists of independent Boolean attributes. The analysis supposes a known target concept and distribution of instances, but includes parameters for the number of training c...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 1998