Random Forest Specifications - Quick Tab

Click this button to display a four-variable list selection dialog box from which you can select the dependent variable, categorical and continuous predictors, and the count variable (optional).

• From the first list, select the dependent variable. If you are analyzing a classification problem with a categorical response variable, the dependent variable must contain text or numeric (integer) codes that identify the class or group to which each case or observation belongs.
• From the second list, select the categorical predictors. Note that these variables must contain text or numeric codes that identify the classes or groups to which each case or observation belongs.
• From the third list, select the continuous predictors.
• From the fourth list, select the count variable. This variable is optional. If selected, it will be used as a case-multiplier in the analysis. Thus, you can analyze input data that have previously been aggregated (tabulated).

Once you have selected a categorical predictor variable, the option for the selection of the factor codes will be available. Click the Factor codes button to display the Select Codes for Independent Variables dialog box, where you can select codes for the categorical factors or predictors. The list of codes can be displayed by clicking the Zoom button. Note that you must select at least two codes for each of the selected categorical factors.

This option is available only if the current analysis is a Classification type (prediction of a categorical or class variable; see also the documentation for the

Random Forest Startup Panel - Quick

tab), and after a categorical dependent variable has been specified. Click the Response codes button to display the Select codes for the categorical response dialog box, where you can select a list of codes for the dependent variable. The list of codes can be displayed by clicking the Zoom button. Note that you must select at least two codes for the selected dependent variable.