I am curious about how the logp values of different variables are calculated when building a Loss Given Default (LGD) model using a decision tree. In other examples I found online, the logp value calculation is always explained with a binary target variable. However, in an LGD model, the target variable is not binary but continuous. How does the logp calculation work when assigning "values" to variables for prediction in this case? Since there is no "good" and "bad" values for the target variable, the classification method and the logp value calculation must be different.
... View more
