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Hi @rasbt,
This Pull Request addresses the issue reported in #759, where the bias_variance_decomp function fails when using Keras models built with the Functional API or in certain TensorFlow versions where the class name is not strictly 'Sequential'.
Key Changes:
Broadened Class Check: Added 'Model' to the list of recognized Keras-like classes (Sequential, Functional, Model) to ensure proper handling of Functional API models.
Improved Logic: Refined the if-else block to decouple the .fit() and .predict() calls. This prevents AttributeError on estimators that return a History object (like Keras) instead of the estimator itself.
Dimensions Preserved: Maintained the original Scikit-learn logic in the else block to ensure that existing unit tests for non-Keras estimators continue to pass without dimension issues.
Verification:
Manual Test: Verified with a Keras Functional API model (it now executes without errors).
Unit Tests: Ran pytest mlxtend/evaluate/tests/test_bias_variance_decomp.py and all tests passed.
Linting: Formatted the code using isort, black, and flake8 (or ruff) to comply with the project's style guide.
Fixes #759