gini

A from-scratch classic that checks recursion plus the split criterion math. The signal is computing impurity correctly, picking the best threshold by information gain, and knowing the stopping rules. Here is a clean recursive implementation.

Trees are the building block of the ensembles that rule tabular ML, so interviewers check you can explain how a split gets chosen and how a lone tree overfits. The Gini-vs-entropy part is a trap: candidates over-weight a choice that barely matters. Here is the answer.