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As an end user, it would be great to be able to interpret the models such as learned features, their importance and overall importance of each channel.
Integration of methods as in https://github.co…
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TL;DR Original List with yet-to-be implemented FE algorithms in https://github.com/parrt/random-forest-importances/issues/54
Seeing https://github.com/interpretml/interpret/issues/364 and https://g…
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近几年explainable AI渐🔥，尤其是最近，有些研究人员将其划分为： explainability 和 interpretability。但翻译中文时，这两词都会被翻译成可解释性。尤其是当我们需要翻译explainability and interpretability of AI时非常困难。而其实他们是有区别的。
区别：
An **interpretable** machine …
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tellurium appears to have limits on the attributes that can be changed via `sedml:changeAttribute`. I'm guessing this applies to `computeChange.target`, `setValue.target`, and `variable.target` as wel…
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i have tried feature_perturbation="interventional" whit backgrouddata and feature_perturbation="tree_path_dependent" without backgrouddata in TreeExplainer, the first example was very slow and finally…
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It would be nice to see an example using the Dask/XGBoost handoff for parallel training and predicting. This is a common question and so would likely have high value.
It would also be useful for t…
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## Detailed Description
We want to be able to easily see what our batches look like and have utilities that plot them to help with debugging and ensuring that our pipelines are doing what we expect.
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It would be nice to have option(s) that highlight the specific location of a point for an individual curve when plotting ICE. The downside with `geom_rug()` in this case is can't trace an observation …
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## 统计历史
The Life, Letters and Labours of Francis Galton, by Karl Pearson
https://galton.org/pearson/
## R 语言
An Introduction to R
https://colinfay.me/intro-to-r/
Outstanding User Interfa…
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