10.19.2

Fixed

• Memory Optimization: Optimized the Python preprocessing pipeline to fix a bug that caused unnecessary memory consumption. A "just-in-time" copy mechanism now prevents large data copies during both fitting and prediction, improving memory safety for all input types.
• Preprocessing Robustness: Addressed a RuntimeWarning: Mean of empty slice that occurred during median imputation in _preprocess_X_fit when a column contained only missing values. The median calculation now gracefully handles such cases.
• Backward Compatibility: Improved __setstate__ to safely load older pickled models by initializing new preprocessing attributes to their correct default types (e.g., []), preventing TypeError exceptions.

Changed

• Code Quality and Maintainability: The entire Python preprocessing pipeline was refactored into a clean fit/transform pattern. This separation of concerns removes boolean flags and significantly improves code clarity, making it easier to maintain and debug.
• Type Hinting: Added comprehensive type hints to all preprocessing methods for better readability and to enable static analysis.

Documentation

• Updated API references and changelog for improved clarity and accuracy regarding the automatic preprocessing of numpy.ndarray and pandas.DataFrame inputs.