Naive Bayes Prediction

Bayesian probability allows prior knowledge and logic to be applied to 

uncertain statements.

p(ci|w) = p(w|ci)p(ci)/p(w)

Pros: works with small amount of data, handles multiple classes

Cons: Sensitive to how the input data is prepared

Works with: Nominal values.

The formulation makes some naive assumptions.

1. independence among the features

2. every feature is equally important

Reference:

https://mahout.apache.org/users/classification/bayesian.html

https://mahout.apache.org/users/basics/creating-vectors-from-text.html

https://gist.github.com/Jossef/e6c8fc0c31f0c2bf036a/download#