Predictive and Specialized Modeling > Naive Bayes > Launch the Naive Bayes Platform
Publication date: 07/08/2024

Image shown hereLaunch the Naive Bayes Platform

Launch the Naive Bayes platform by selecting Analyze > Predictive Modeling > Naive Bayes.

Figure 8.6 Naive Bayes Launch Window 

Naive Bayes Launch Window

For more information about the options in the Select Columns red triangle menu, see Column Filter Menu in Using JMP.

The Naive Bayes launch window provides the following options:

Y, Response

The categorical response column whose values are the classes of interest.

X, Factor

Categorical or continuous predictor columns.

Weight

A column whose numeric values assign a weight to each row in the analysis.

Freq

A column whose numeric values assign a frequency to each row in the analysis.

Validation

A numeric column that defines the validation sets. This column should contain at most three distinct values:

If the column has three unique values, then:

rows with the smallest value are used for the Training set.

rows with the middle value are used for the Validation set.

rows with the largest value are used for the Test set.

If the column has two unique values, then only Training and Validation sets are used.

If the validation column has more than three levels, the rows that contain the smallest three values define the validation sets. All other rows are excluded from the analysis.

The Naive Bayes platform uses the validation column to train and evaluate the model. For more information about validation, see Validation in JMP Modeling.

If you click the Validation button with no columns selected in the Select Columns list, you can add a validation column to your data table. For more information about the Make Validation Column utility, see Make Validation Column.

By

A column or columns whose levels define separate analyses. For each level of the specified column, the corresponding rows are analyzed using the other variables that you have specified. The results are presented in separate reports. If more than one By variable is assigned, a separate analysis is produced for each possible combination of the levels of the By variables.

Validation Portion

Specifies the portion of the data to be used as the Validation set.

Note: If neither a Validation column or a Validation Portion is specified in the launch window and if there are excluded rows, these rows are treated as a Validation set. For more information about validation see Validation in JMP Modeling.

Prior Bias

Sets the prior bias value. This value is divided by the number of response levels and then the resulting quantity is added to the counts to ensure non-zero rate estimates.

Want more information? Have questions? Get answers in the JMP User Community (community.jmp.com).