Auto-sklearn
Offers automated machine learning with scikit-learn integration and includes hyperparameter tuning, unlike Lazypredict which uses untuned basic models.
TPOT
Uses genetic programming to optimize machine learning pipelines, providing automated tuning and feature engineering beyond Lazypredict's baseline comparisons.
H2O AutoML
Provides automated model building and ranking with support for advanced algorithms and tuning, whereas Lazypredict focuses on quick baseline model comparisons.
AutoGluon
Supports multi-modal automated machine learning including tabular, text, and image data, offering broader capabilities than Lazypredict's tabular focus.
FLAML
A frugal automated machine learning library that balances accuracy and efficiency with automated tuning, contrasting with Lazypredict's untuned model approach.