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- [ ] [GRANDE: Gradient-Based Decision Tree Ensembles for Tabular Data | OpenReview](https://openreview.net/forum?id=XEFWBxi075)
# GRANDE: Gradient-Based Decision Tree Ensembles for Tabular Data
## …
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Hi,
First of all thank you for the package! In "Fitting Prediction Rule Ensembles with R Package pre" I noticed that it should be possible to use random forest for rule induction by setting mtry and …
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## 論文リンク
https://arxiv.org/abs/1802.03888
## 公開日(yyyy/mm/dd)
2018/02/12
## 概要
機械学習の解釈可能性に関する SHAP 値を XGBoost や LightGBM に対して効率的に計算したり実験で確認したという論文。ensemble tree でよく使われる importance の指標が、あるモデルから…
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I'm sat in your AMS talk, and this package looks really cool!
### Is your feature request related to a problem?
I made the [xarray-datatree package](https://github.com/xarray-contrib/datatree), …
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Currently, the examples here https://github.com/LorenzoCazzaro/Verifiable-Learning-Robust-Tree-Ensembles/tree/master/src/carve point to some non-existing files. We should fix this.
See here https:/…
jermp updated
3 months ago
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Currently in `readvar.py`, the input variables are reduced over the time dimension (spanning a duration of 10 years) to calculate statistics like mean and std. This significantly reduces the size of t…
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### Issue Description
I'm struggling with some inconsistencies between different tree based models when passing `'probability'` vs `'predict_proba'` as the `model_output` to a shap `TreeExplainer`.…
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It would be great to support some basic CNNs. In a manner that is just as easy to install and use as the tree-based-ensembles that we have now. That means that there should be a core module that suppo…
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Please consider supporting "soft" decision tree ensembles like those in the SoftBart R package. That seems pretty on-point as a smoothing technique which would be exciting to have in a distributional …
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