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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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Implement bagging ensemble model and find it's accuracy.
Implements part of story #101
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It would be useful to allow the user to run true cross-validation out of the box in TabularPredictor.
True cross-validation would ensure that the validation data is never used for any early stoppin…
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## Concept
Training several models in production (split 80/20/0) with different seeds, the idea is to average all predictions to generate a more reliable soft prediction (ie: bagging ensemble).
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# Tweet summary
Train multiple classifiers with bootstrap undersample data set on imbalanced data.
# Useful link
https://www.svds.com/learning-imbalanced-classes/#fn2
https://imbalanced-learn.or…
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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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### Is there an existing issue for this?
- [X] I have searched the existing issues
### Feature Description
Combine multiple models using ensemble techniques such as bagging, boosting, or stacking. …
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모델 | Accuracy | AUROC
-- | -- | --
LightGBM | 0.4366438356164384 | 0.6439185931199092
XGBoost | 0.4440639269406393 | 0.648953293189703
Ensemble | 0.4394977168949772 | 0.6523183340251395
Ensem…
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I would like to request this library to have ensemble learning classes such as one for stacking, most libraries work with scikit learn but not with turicreate.
Thanks
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### Discussed in https://github.com/orgs/ultralytics/discussions/14959
Originally posted by **vinycecard** August 5, 2024
I'm training AIs separately, one for each type of identification (e.g…