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 prior probabilities or 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, before any splits. The data in this table match the data in the root
node of the tree.
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 select a tree with a test set instead of with cross-validation,
Minitab displays results for the Training and Test sets for comparisons. Use
the Test results to evaluate the performance of the classification tree. The
training data set is used to grow and prune the tree, while the test set is
used to select the tree.
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.
