The Response Information table contains the class identifier, the
counts, and the percentage for each level of the response variable. Minitab
displays either the Binary Response Information table or the Multinomial
Response Information table, depending on the number of levels in your response.
If you specify class weights or individual case weights, Minitab also displays
this information.
With cross-validation as the model selection method
The Response Information table shows the breakdown of response data into
levels.
Variable
Name of the response variable.
Class
Levels of the response variable.
Count
Number of observations at each level of the response variable.
%
Percentage of observations at each level of the response variable.
With separate test set as the model selection method
If you use a test set instead of cross-validation, Minitab displays results
for the Training and Test sets for comparisons. Use the Test results to
evaluate the performance of the TreeNet® model. Use the Training results to
evaluate whether the model overfits the training data.
Training Count
Number of observations at each level of the response variable for the
training data set.
Training %
Percentage of observations at each level of the response variable for
the training data set.
Test Count
Number of observations at each level of the response variable for the
test data set.
Test %
Percentage of observations at each level of the response variable for
the test data set.