This workflow shows 2 examples of parameter optimization in a decision tree and in a logistic regression. In the decision tree we optimize the minimum number of records per node within a range [2,15] with step 1. In the Logistic Regression we optimize step size in (0,1] step =0.1 and variance in (0, 5] step = 0.1
This is a companion discussion topic for the original entry at https://kni.me/w/ctcDEiPLQYhzHIwr