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

Also charts the top 25 variables in the model.