Note
This command is available with the Predictive Analytics Module. Click here for more information about how to activate the module.
The boxplot shows the difference between the actual and fitted values. Points that are more than 1.5 times the interquartile range from the nearest quartile have individual symbols.
Interpretation
Ideally, the residuals are all close to 0, relative to the scale of the response variable. When the analysis uses a validation method, the results include separate plots for the training data and for the validation results. The performance of the tree from the validation results is a typically a better representation of how the tree performs for new data. You should investigate large differences between the validation results and the training data.
These boxplots show that the IQR is much larger for the test data set than for the training data set. This difference suggests that the performance of the model on new data is not as good as the performance of the model on the training data. Also, the large residuals, which are represented by individual symbols, can indicate that the model does not fit all of the data well.
