pycaret 集成学习 英文

Pycaret is a powerful open-source machine learning library for Python that simplifies the process of building, testing, and deploying machine learning models. It provides an extensive suite of tools for data preprocessing, model selection, and visualization, all in a user-friendly and automated manner. Pycaret's "ensemble learning" functionality, which falls under the umbrella of integrated learning, allows users to combine multiple models into a single prediction, improving performance through techniques like stacking, blending, or boosting.

In ensemble learning, pycaret:

1. **Model Stacking (StackingCV)**: Combines the predictions of multiple base models, where each base model is trained independently, and then uses a meta-model to make the final prediction based on their outputs.
2. **Blending (blend_models)**: Averages the predictions of multiple models without training a meta-model, simply taking the average or weighted average of the predictions.
3. **Ensemble Grid Search (ensemble GridSearchCV)**: Automates the process of creating and evaluating ensembles by tuning hyperparameters for each base model and selecting the best combination.
4. **Super Learner**: Similar to stacking, pycaret employs a "super learner" approach where it trains a selection of base learners and combines them to create a superior predictive model.