Question 55
Consider the following code snippet that trains a Decision Tree classifier using scikit-learn:
A node in the trained decision tree is split only if both of the following conditions are satisfied: • The node contains at least min_samples_split samples. • Each child node created after the split contains at least min_samples_leaf samples. Assume node (N) is a non-leaf node being considered for splitting. In which of the following cases will the split at node (N) be allowed?
Node (N) contains 15 samples. After splitting, the left child has 9 samples and the right child has 6 samples.
Node (N) contains 6 samples. After splitting, the left child has 4 samples and the right child has 2 samples.
Node (N) contains 12 samples. After splitting, the left child has 3 samples and the right child has 9 samples.
Node (N) contains 8 samples. After splitting, the left child has 4 samples and the right child has 4 samples.