Workspace Node: Random Forest Classification - Specifications - Stopping Condition Tab

In the Random Forest Classification node dialog box, under the Specifications heading, select the Stopping Condition tab to access options that control the end of training. Specifically, there are stopping conditions to determine if training should be terminated before the full number of trees are added to the Random Forest model.

Element Name Description
Enable advanced stopping condition Select this check box to enable early stopping of the Random Forest training algorithm, i.e., stop adding trees before the full number of trees are added to the model. Selecting this option will make the rest of the controls on this tab available.
Cycles to calculate mean error Specifies the number of cycles across which improvement is measured. The Random Forest algorithm may demonstrate noise on the training and test errors. Therefore, it is not usually a good idea to halt training on the basis of a failure to achieve the desired improvement in error rate over a single cycle. This field specifies a number of cycles over which the error rates are monitored for improvement. Training is only halted if the error fails to improve for that many cycles.
Percentage decrease in training error Specify a minimum percentage of improvement (drop) in error that must be made; if the rate of improvement drops below this level, training is terminated.

Options / C / W. See Common Options.

OK Click the OK button to accept all the specifications made in the dialog box and to close it. The analysis results will be placed in the Reporting Documents node after running (updating) the project.