Discriminative Training of Chow-Liu tree Multinet Classifiers. Huang, Kaizhu Dept. of Computer Science and Engineering, CUHK. Outline. Background Classifiers Discriminative classifiers Generative classifiers Bayesian Multinet Classifiers Motivation
Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.
Dept. of Computer Science and Engineering,
SVM ClassifiersDiscriminative Classifiers
Example of Missing Information:
From left to right: Original digit, Cropped and resized digit, 50% missing digit, 75% missing digit, and occluded digit.
TJT: a generative model
Discriminative Classifiers Classifiers
HMM and GMM
2.How our work relates to other work?
Jaakkola and Haussler NIPS98
Difference: Our method performs a reverse process:
From Generative classifiers to Discriminative classifiers
Beaufays etc., ICASS99, Hastie etc., JRSS 96
Difference: Our method is designed for Bayesian Multinet Classifiers, a more general classifier.
Pre-classified dataset Classifiers
for Class I
for Class 2
Estimate the distribution P1 to
approximate D1 accurately
Estimate the distribution P2 to
approximate D2 accurately
Use Bayes rule to
perform classificationProblems of Bayesian Multinet Classifiers
Comments: This framework discards the divergence information between classes.