Model Summary

The model summary shows a couple of positive signs:

• The percentage of incorrect predictions is roughly equal across training, testing, and holdout samples.
• The estimation algorithm stopped because the error did not decrease after a step in the algorithm.

This further suggests that the original model may have, in fact, overtrained and that the problem was solved by adding a testing sample. Of course, the sample sizes are relatively small, and perhaps we should not read too much into the swing of a few percentage points.

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