Select menu Stats | Multivariate Analysis | Trees | Random Classification Forest
Use this to form a random classification forest. This uses the BCFOREST procedure to randomly select variates and a subset of units of the training data set, and creates optimal Classification Trees for each selection. The identification is then performed using the consensus of the identifications from the individual trees. See the help on the Classification Trees menu for more information on how the trees are produced.
- After you have imported your data, from the menu select
Stats | Multivariate Analysis | Trees | Random Classification Forest.
- Fill in the fields as required then click Run.
This lists data structures appropriate to the current input field. The contents will change as you move from one field to the next. Double-click a name to copy it to the current input field or you can type the name.
Specify a factor for the groupings of the individuals.
Specifies the independent (x) variables available for constructing the tree. The variables can be factors or variates. You can transfer multiple selections from Available data by holding the Ctrl key on your keyboard while selecting items, then click to move them all across in one action.
Save forest in:
Specifies an identifier name to save the resulting forest in. The forest will be saved within a Genstat pointer data structure.
The button opens the Save dialog which allows you to store or display the out of bag identifications, out of bag error, importance of the variables, confusion matrix and votes from the forest.
The button opens the Further Output dialog which allows you to display information on the tree from the analysis.
The button opens the Identifications dialog which allows you to store the identifications and group probabilities for the current data set or for a new set of observations.
|Controls whether to keep the dialog open when you click Run. When the pin is down the dialog will remain open, otherwise when the pin is up the dialog will close.
|Restore names into edit fields and default settings.
|Clear all fields and list boxes.
|Open the Help topic for this dialog.
- Random Classification Forest Options dialog.
- Random Classification Forest Further Output dialog.
- Random Classification Forest Save dialog.
- Random Classification Forest Identifications dialog.
- Classification Trees menu.
- Random Regression Forest menu.
- K Nearest Neighbours menu.
- Regression Trees menu.
- Discriminant analysis menu.
- Canonical variates analysis menu.
- Stepwise Discriminant Analysis menu.
- BCFOREST procedure.
- BCFDISPLAY procedure.
- BCFIDENTIFY procedure.