How-To
Random ForestsĀ® Classification
Before you start
Overview
Data considerations
Example
Example of prediction
Perform the analysis
Enter your data
Specify the class weights
Specify the validation method
Select the options
Select the graphs to display
Select the results to display
Store statistics
Predict new results
Predict new results
Select the prediction results to display
Store prediction statistics
Interpret the results
Method table
Response information table
Optimization of hyperparameters
Misclassification rate vs number of trees plot
Model summary table
Relative variable importance chart
Confusion matrix
Misclassification table
Receiver operating characteristic (ROC) curve
Gain chart and Lift chart
Prediction table
Methods and formulas
Methods
Response information
Model summary
Confusion matrix
Misclassification table
ROC curve
Gain chart
Cumulative lift chart
Lift chart