An Evaluation Study for the Impact of Discretization Methods on the Performance of Naive Bayesian Classifiers with Prior Distributions
碩士 === 國立成功大學 === 工業與資訊管理學系專班 === 98 === Na?ve Bayesian classifiers are widely employed for classification tasks, because of their computational efficiency and competitive accuracy. Discretization is a major approach for processing continuous attributes for na?ve Bayesian classifiers. In additio...
Main Authors: | Nai-YuYang, 楊乃玉 |
---|---|
Other Authors: | Tzu-Tsung Wong |
Format: | Others |
Language: | zh-TW |
Published: |
2010
|
Online Access: | http://ndltd.ncl.edu.tw/handle/40262687553999457567 |
Similar Items
-
Hybrid discretization methods for naive Bayesian classifiers with priors
by: Chuan-YuTsai, et al.
Published: (2013) -
Improving the performance of Naive Bayes Classifier by using Selective Naive Bayesian Algorithm and Prior Distributions
by: Liang-Hao Chang, et al.
Published: (2009) -
A measure for the appropriateness of prior distributions in naive Bayesian classifiers
by: Shi-geng Chen, et al. -
Individual Attribute Prior Settings for Improving the Performance of Naive Bayesian Classifiers
by: Chi-Fang Lin, et al.
Published: (2007) -
Generalized Dirichlet Priors for Naïve Bayesian Classifiers with Multinomial Models in Classifying Gene Sequence Data
by: Mu-YingWu, et al.
Published: (2012)