Guidelines for communication

Now that we have covered debugging, monitoring and iterative testing of predictive models, we close with a few notes on communicating results of algorithms to a more general audience.

Translate terms to business values

In this text, we frequently discuss evaluation statistics or coefficients whose interpretations are not immediately obvious, nor the difference in numerical variation for these values. What does it mean for a coefficient to be larger or smaller? What does an AUC mean in terms of customer interactions predicted? In any of these scenarios, it is useful to translate the underlying value into a business metric in explaining their significance to non-technical colleagues: for example, coefficients in a linear model represent the unit change in an outcome (such as revenue) for a 1-unit change in particular input variable. For transformed variables, it may be useful to relate values such as the log-odds (from logistic regression) to a value such as doubling...