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could be random forests, boosted regression trees, or similar
would have the benefit of considering interactions among explanatory variables more effectively
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The following case should be an error: train a model on some data then call `predict` with completely unrelated data (i.e. no features in common with the training set).
All of turicreate's regress…
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# Predict housing prices in Austin TX with tidymodels and xgboost | Julia Silge
More xgboost with tidymodels! Learn about feature engineering to incorporate text information as indicator variables fo…
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Installation of XGBoost module is complicated, so i provide the link below, plz follow the description carefully.
https://www.ibm.com/developerworks/community/blogs/jfp/entry/Installing_XGBoost_For…
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An ensemble of boosted trees can be trivially multi-threaded at inference time. We should support an option to set the threads for model inference for ingest.
The solution may be to support a "mode…
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## Description
Allow users to write their own classifiers.
## Scenario
If a user wanted to try using a different classifier, such as SVM or Gradient Boosted Trees, they would be able to by wr…
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https://explained.ai/rf-importance/
Are you aware of this method and its benefits?
https://scikit-learn.org/stable/modules/generated/sklearn.inspection.permutation_importance.html?highlight=perm…
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Elastic ML utilizes Shapley Values to determine feature importance.
For boosted regression trees, a simple form of this is to know the number of samples from the training data that "landed" in eac…
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I am reading through skopt's docs and it seems like there might be a typo in the description for both `gbrt_minimize` and `forest_minimize`.
**gbrt_minimize:**
```
Gradient boosted regression tr…
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Hi,
many thanks for your very useful, nicely built and intuitive tool, really. You've said somewhere that maybe forestFloor may handle boosted trees from xgboost, do you have any news regarding this …