# Top 2-way interaction strength tables for Fit Model and Discover Key Predictors with TreeNet® Regression

###### Note

Find interpretation guidance for the interaction strength tables.

The top 2-way interaction strength tables identify the pairs of variables that have the strongest interactions. The interaction tables display the % of total squared error and/or the % of squared error for the strongest 2-way interactions. Use the % of total squared error to describe the strength of the interaction relative to the variation in the data. Use the % of squared error for the specific pair of variables to describe the strength of the interaction relative to the strength of the main effects of the variables.

Interactions are not possible when a tree has only 2 terminal nodes. Thus, the maximum terminal nodes per tree must be 3 or larger. You can set this on the Options subdialog.
###### Note

Minitab does not display the interaction tables if all interactions have a % of total squared error or a % of squared error less than 10%.

## Interpretation

In this example, the eight strongest 2-way interactions are the same for both tables; however, the ordering varies slightly. In the first table, the interaction between Annual Income and Front End Ratio is the strongest 2-way interaction. The percent of total squared error is 11.71977 which means that 11.71977% of the total squared error is explained by the main effects of Annual Income and Front End Ratio and their 2-way interaction effect.

For the same 2-way interaction between Annual Income and Front End Ratio, the percent squared error for the predictor pair with main and interaction effects is 19.73464%.

To calculate, 19.73464% = Component 3 / ( Component 1 + Component 2 + Component 3) * 100%
• Component 1 = the squared error explained by the first main effect, Annual Income
• Component 2 = the squared error explained by the second main effect, Front End Ratio
• Component 3 = the squared error explained by the interaction between Annual Income and Front End Ratio and their main effects
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