Practical Predictive Analytics

Interpreting the output

The output from the summary gives a good sense of the importance of each variable as an individual predictor. All of the accuracy measures range from 67.61% to 68.56%, so there is no obvious one single variable which can predict being frisked much better than the others.

However, the top ranked variable is sex with a 68.56% accuracy rate. The one simple rule that will classify the outcome into frisked or nonfrisked is:

If sex is male or unknown, then the outcome was predicted correctly 68.56% of the time.

This is reflected in the following two manually calculated contingency tables, in which an asterisk * signifies a correct classification (the following background is green). I added the second contingency table manually, ...