Michael Crown
data scientist

Gaussian Naive Bayes Classifier

With Continuous and Discrete or Categorical Functionality

A lean and efficient program for fitting Naive Bayes classifiers to either qualitative or quantitative data. In the latter case, a Gaussian distribution is used to compute probability densities. Some minor refactoring is planned, including addition of other distributions. The functionality for qualitative data has not yet been extensively tested.


  • Works with qualitative or quantitative data
  • Uses matrix operations wherever possible for efficient operation
  • Return predictions as either predicted classes (predict) or posterior probability densities (p_predict).
  • Uses log probabilities for quantitative data.
  • A scoring function that returns
    • Accuracy
    • Precision
    • Recall
    • F1
    • Easily modified to compute other metrics like specificity or fall-out.

Get the code here