bayesian classification

Bayesian ClassifierGang Tao

Algebraic GeometryComplex Analysis factal Differential equationGeometry

Dynamical SystemCombinatorial Mathematics

StatisticsComputational mathematics

Bayes Theorem

Bayes Theorem

Diachronic Interpretation

H -> HypothesisD -> DataP(H) -> Prior ProbabilityP(H|D) -> Posterior ProbabilityP(D|H) -> LikelihoodP(D) -> Normalizing Constant

Bayes Theorem

Original Belief Observation+ = New Belief

Bayes and Occam’s Razor

“All Models are wrong, but some of them are better

than the others”

Model Complexity

Naive Bayes

“Naive” because it is based on independence assumptionAll the attributes are conditional independent given the class

Naive Bayes Classifier

How to build a Bayesian Classifier for prediction

Prepare Data Features Extraction

Select Distribution

Model

Calculate the Probability for each attributes

Multiply All Probabilities

Label with highest

Probability

Advantage VS. Disadvantage

PowerfulEfficient in Space and TimeIncremental Trainer

SimpleIndependant AssumptionProbability are not relevant

Application of Bayesian Classifier

Spam Email Filter

Natural Language Processing

Word Segmentation

Spell Checking

Machine Translation

Pattern Recognition

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