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
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.