Categorical ResponsesAn asterisk marks the model for the value K that has the smallest misclassification rate. The report for a categorical response contains the following columns:
Number of nearest neighbors used in the model. K ranges from 1 to the Number of Neighbors, K that you specified in the launch window.
Proportion of observations misclassified by the model. This is calculated as Misclassifications divided by Count. The model with the smallest misclassification rate is marked with an asterisk. If there are tied misclassification rates, the model with the smallest K is marked with the asterisk.
A confusion matrix is shown for the model with the smallest Misclassification Rate (or the model with the smallest K if there are ties for the smallest misclassification rate). If you use validation, confusion matrices for the validation and test sets appear. A confusion matrix is a two-way classification of actual and predicted responses. Use the confusion matrices and the misclassification rates to guide your selection of a model.