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### Feature Name
Adding Ensemble MethodsVisualizations
### Feature Description
Introduce ensemble methods such as bagging, boosting, and stacking. These techniques combine multiple models to improv…
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### Is this a unique feature?
- [X] I have checked "open" AND "closed" issues and this is not a duplicate
### Is your feature request related to a problem/unavailable functionality? Please describe.…
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### Have you completed your first issue?
- [X] I have completed my first issue
### Guidelines
- [X] I have read the guidelines
- [ ] I have the link to my latest merged PR
### Latest Merged PR Lin…
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There are some different ways to do this:
# Use metalearner as base learners, keep level-one frame and pass this as the training frame
# Use the blending_frame instead
Requested on StackOverflow:…
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Hi Viewer,
I am performing predictions using both `XGBoost` and `Random Forest` models on a dataset, but I consistently observe that the Random Forest model achieves better `R²` scores and `correla…
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### Describe the issue linked to the documentation
Currently most ensembling methods in `scikit-learn` such as [bagging methods](https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.Bag…
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Dear developers,
I am using a stacking ensemble model whose base-classifiers in the first layer are tree models, but the meta-classifier in the second layer is LR. I tried to use SHAP v0.40.0 to ca…
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Hi everyone,
First of all, thank you for the well-documented library.
I have a question regarding the use of TabularPredictor for creating a stacking ensemble model. I’m unsure how AutoGluon handl…
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The following paper by Rich Caruana
http://www.niculescu-mizil.org/papers/shotgun.icml04.revised.rev2.pdf
presents an simple greedy algorithm to stack models.
It is reported by many people to be an e…
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## Feature
Similar to https://github.com/tidymodels/probably/issues/159.
When producing a stacked ensemble of predictions, although the base models may have been trained using importance weights…