An add-in for computing Naive Bayes probabilities, developed by Ian Cox (Ian@JMP) and BradyBrady for academic purposes.
1. Open a data table with a categorical outcome and categorical predictors (Note: All variables must be coded as Character and Nominal).
2. Specify the variables, and click OK
A data table, with calculations to compute the predicted probabilities and the most likely outcome. Note that the most likely outcome is based on a cutoff of 0.50.
A cell plot, which provides a graphical representation of the results
An interactive dialog for computing predicted probabilities for particular features or conditions
3. Select the features of interest, and click Compute Probabilities.
Updated 10/2/2015: Will now accept numeric columns, but these columns must be coded as Nominal. The Value Labels column property must be removed prior to using the add-in. Continuous predictors must binned or recoded (and require the nominal modeling type).