
Understanding Models
Permutation importance can lose clarity when features overlap
Read permutation importance cautiously when model inputs carry overlapping information, and distinguish a small score drop from proof that a feature is useless.

Read permutation importance cautiously when model inputs carry overlapping information, and distinguish a small score drop from proof that a feature is useless.

Read an AI model card for intended uses, evaluation conditions and limitations, then identify what still needs testing in your own application.