This command is available with the Predictive Analytics Module. Click here for more information about how to activate the module.
When you use Discover Best Model (Continuous Response) to identify the best model type, Minitab Statistical Software produces results for the model with the best value of the accuracy criterion for the analysis, such as the maximum R^{2}. Minitab lets you explore results for other models and other types of models. For example, if another type of model produces similar prediction accuracy, you can determine whether the same predictors are important in each type of model.
The available options depend on the type of model. For multiple regression and CART^{®} models, you can examine the results for the best model from the search. For Random Forests^{®},TreeNet^{®}, and MARS^{®} models you can examine results from any of the models in the search. For Random Forests^{®}, TreeNet^{®} and MARS^{®} models, you can also tune the hyperparameters to look for combinations that produce even better values than the hyperparameters in the search.
Select an existing model to produce results for one of the models from the search. Specify hyperparameters to fit new models to look for combinations of hyperparameters that improve the performance of the model.
In the search for the best type of model, the analysis produces up to 3 Random Forests^{®} models with different minimum sizes for internal nodes. Select a model from the list and click Display Results to produce results for that model.
Select an existing model to produce results for one of the models from the search. Specify hyperparameters to fit new models to look for combinations of hyperparameters that improve the performance of the model.
In the search for the best type of model, the analysis produces a TreeNet^{®} model for each combination of hyperparameters. Select a model from the list and click Display Results to produce results for that model.
The analysis requires that you specify all of the hyperparameters. Click Display Results to evaluate the hyperparameters for the new models. The results include a table that compares the optimality criteria for the different combinations of hyperparameters and the results for the model with the best value of the accuracy criterion for the analysis, such as the maximum R^{2}.
Select an existing model to produce results for one of the models from the search. Specify hyperparameters to fit new models to look for combinations of hyperparameters that improve the performance of the model.
In the search for the best type of model, the analysis produces a MARS^{®} model with each number of basis functions in the search. Select a model from the list and click Display Results to produce results for that model.
Allow predictor interactions up to order that you specify. An interaction means that the effect of a predictor depends on the value of other predictors. For example, the rate at which grain dries in an oven depends on the time in the oven, but the effect of time depends on the temperature of the oven. The time and temperature variables interact.
Select Results for multiple regression model and click Display Results to produce the results for the best multiple regression model from the search for the best type of model.
Select Results for CART® model and click Display Results to produce the results for the best CART^{®} model from the search for the best type of model.