Naive Bayesian classifier based on p-values.
| Autor: | Chih-Hsuan Chu, 朱芷萱 |
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| Rok vydání: | 2016 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 104 Naive Bayesian classifier estimates the joint likelihood of a testing instance as the product of the likelihood for each individual feature estimated from the training data and then applies Bayes' rule to calculate the posterior distribution of the class. In addition to the likelihood, p-value in statistical hypothesis testing which reflects the discrepancy between the observed sample and the expected sample under some hypothesis serves similar purpose and will be used to replace the likelihood in the proposed Bayesian classifier. We alleviate the naive independence assumption among features for each class by applying principal component analysis to obtain the uncorrelated transformed features. The joint p-value in the proposed Bayesian classifier which is the product of the p-value associated with each transformed feature estimated from the training data is used to calculate, in conjunction with the prior distribution, the posterior p-value for the testing instance. Empirical results demonstrate substantial improvement on the classification accuracy when compared with the existing classification methods. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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