Gauss Naive Bayes

Description: Bayesian Probability Theory is a field of statistics that has to do with conditional inference. Like many other classification models, the Naive Bayes model depends upon referencing a training dataset. However, unlike the KNN-Classifier and others, the Bayesian probability model relies on designating probabilities to all possible outcomes, assuming all features are independent (Naive) and abide by a certain distribution (usually a normal distribution). That is, each possible class is considered with a non-zero probability.

Presenter: Sam Showalter

Date: November 20, 2017

Location: Julian 147

GitHub Link: Naive_Bayes