Select an alternative model from Discover Key Predictors with TreeNet^® Classification

Run Predictive Analytics Module > TreeNet® Classification > Discover Key Predictors. Click the Select an Alternative Model button after the Predictor Elimination table.

Note

This command is available with the Predictive Analytics Module. Click here for more information about how to activate the module.

Overview

When you use Discover Key Predictors to remove the least important predictors, Minitab Statistical Software produces results for the model with the best value of the accuracy criterion for the analysis, such as the minimum average –loglikelihood. Minitab lets you explore other models from the sequence that led to the identification of the optimal model. Generally, you select an alternative model if another model has a value of the criterion close to the best, but with fewer predictors. A model with fewer predictors is easier to interpret, can have better prediction accuracy, and allows you work with a smaller number of predictors.

For example, the following model selection table has 13 steps. The model with the least average –loglikelihood is the model with all of the predictors. The model at step 11 has an average –loglikelihood that is relatively close to the best value. The model at step 11 has 3 predictors. The full results from the model at step 11 are also of interest.

Model Selection by Eliminating Unimportant Predictors

Test

Model	Optimal Number of Trees	Average -Loglikelihood	Number of Predictors	Eliminated Predictors
1	268	0.273936	29	None
2	268	0.274186	27	Foam Stability, Bulk Density
3	234	0.273843	26	Least Gelation Concentration
4	233	0.274350	25	Oven Mode 2
5	232	0.274943	24	Kiln Method
6	273	0.275553	23	Oven Mode 1
7	244	0.274811	22	Mix Speed
8	268	0.274258	21	Oven Mode 3
9	272	0.274185	20	Resting Surface
10	232	0.274077	19	Bake Temperature 3
11	287	0.273598	18	Mix Tool
12	227	0.274358	17	Bake Temperature 1
13	276	0.275374	16	Rest Time
14	272	0.276082	15	Water
15	268	0.275595	14	Caustic Concentration
16	268	0.277810	13	Swelling Capacity
17	253	0.276436	12	Emulsion Stability
18	231	0.276159	11	Emulsion Activity
19	268	0.273537	10	Water Absorption Capacity
20	260	0.273455	9	Oil Absorption Capacity
21	299	0.272848	8	Flour Protein
22	278	0.272629	7	Foam Capacity
23*	299	0.267184	6	Flour Size
24	297	0.288621	5	Bake Temperature 2
25	234	0.330342	4	Dry Time
26	290	0.305993	3	Gelatinization Temperature
27	245	0.534345	2	Bake Time
28	146	0.599837	1	Kiln Temperature

Perform the analysis

Click Select an Alternative Model in the output. A dialog box opens that shows a plot of the criterion against the number of eliminated predictors and a table that summarizes the steps.

Compare the criteria

To select an alterative model, click a point on the graph or a row in the table. Press Display Results to create the results for that model.

Once you display the results, you can click a button in the output to tune the hyperparameters of the model or to make predictions from the model. For more information, go to Select hyperparameter values to evaluate from the results for TreeNet® Classification or Predict new results for Fit Model and Discover Key Predictors with TreeNet® Classification.

Tip

To compare the output of two different analyses or reports, right-click the second item in the Navigator and choose Open in Split View.