# Prior Probabilities

For CRT and QUEST trees with categorical dependent variables, you
can specify prior probabilities of group membership. **Prior probabilities** are
estimates of the overall relative frequency for each category of the
dependent variable prior to knowing anything about the values of the
independent (predictor) variables. Using prior probabilities helps
to correct any tree growth caused by data in the sample that is not
representative of the entire population.

**Obtain from training sample (empirical priors).** Use this
setting if the distribution of dependent variable values in the data
file is representative of the population distribution. If you are
using split-sample validation, the distribution of cases in the training
sample is used.

*Note*: Since cases are randomly assigned to the training
sample in split-sample validation, you won't know the actual distribution
of cases in the training sample in advance. See the topic Validation for
more information.

**Equal across categories.** Use this setting if categories
of the dependent variable are represented equally in the population.
For example, if there are four categories, approximately 25% of the
cases are in each category.

**Custom.** Enter a non-negative value for each category of
the dependent variable listed in the grid. The values can be proportions,
percentages, frequency counts, or any other values that represent
the distribution of values across categories.

**Adjust priors using misclassification costs.** If you define
custom misclassification costs, you can adjust prior probabilities
based on those costs. See the topic Misclassification Costs for
more information.

Profits and Value Labels

This dialog box requires defined value labels for the dependent variable. It is not available unless at least two values of the categorical dependent variable have defined value labels. See the topic To specify value labels for more information.

To Specify Prior Probabilities

This feature requires the Decision Trees option.

- From the
menus choose:
- In the main Decision Tree dialog box, select a categorical (nominal, ordinal) dependent variable with two or more defined value labels.
- For the growing method, select CRT or QUEST.
- Click Options.
- Click the Prior Probabilities tab.