Description

Add out-of-bag (OOB) score estimation to cuML's Random Forest implementation, similar to sklearn's oob_score_ attribute. See the sklearn example for reference on how OOB scoring is used in practice.

Rationale

OOB scores provide a built-in cross-validation mechanism that estimates generalization performance without requiring a separate validation set, useful for rapid model evaluation.

Original issue: #3361