Random Forest Classification Details—Multinomial
The Model Detail screen includes the following information for multinomial Random Forest Classification models:
Metrics
Provides training, test, and n-fold data for the following:
- Mean squared error (MSE)
- Root mean squared error (RMSE)
- Number of observations
- R-squared (R2)
- Logloss
- Mean per class error
Confusion Matrix
Illustrates the performance of a model on a set of training, test, and n-fold data for which the true values are known.
Variable Importances
Provides importance values for each variable using the following metrics:
- Relative importance
- Scaled importance
- Percentage