Here are the slides I use for my course about “Naive Bayes Classifier”. The main originality of this presentation is that I show it is possible to extract an explicit model based on the calculations of the conditional distributions. This makes highly easier the deployment of the model in real case studies. This aspect is commonly unknown. The feature selection problem in the context of Naive Bayes Classifier learning is also highlighted.
Keywords: machine learning, supervised methods, naive bayes, independence assumption, independent feature model, feature selection, cfs
Slides: Naive Bayes classifier
References:
T. Mitchell, "Generative and discriminative classifiers: naive bayes and logistic regression", in "Machine Learning", McGraw Hill, 2010; Draft of January 2010.
Wikipedia, "Naive Bayes classifier".
