Specify the default settings for Discover Best Model (Binary Response)

File > Options > Predictive Analytics > Discover Best Model (Binary Response)

Specify the default methods for Discover Best Model (Binary Response). The changes you make to the defaults remain until you change them again, even after you exit Minitab.

Criterion for selecting the best model

Choose the method to generate your optimal model. You can compare the results from several methods to determine the best choice for your application.
  • Maximum loglikelihood: The maximum likelihood method finds the maximum of the likelihood functions for the data.
  • Maximum area under ROC curve: The maximum area under ROC curve method works well across many applications. The area under the ROC curve measures how well the model ranks rows from most likely to produce an event to least likely to produce an event.
  • Minimum misclassification rate: Select this option to display results for the model that minimizes the misclassification rate. The misclassification rate is based on a simple count of how often the model predicts a case correctly or incorrectly.

Individual tree complexity parameter for TreeNet® Classification models

Choose one of the following to limit the size of the trees.
  • Maximum terminal nodes per tree: Enter a value between 2 and 2000 to represent the maximum number of terminal nodes of a tree. Usually, 6 provides a good balance between calculation speed and the investigation of interactions among variables. A value of 2 eliminates the investigation of interactions.
  • Maximum tree depth: Enter a value between 2 and 1000 to represent the maximum depth of a tree. The root node corresponds to a depth of 1. In many applications, depths from 4 to 6 give reasonably good models.