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Thanks for great work! We have an open source machine learning library called SMILE (https://github.com/haifengl/smile). We have incorporated your benchmark (https://github.com/haifengl/smile/blob/mas…
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This is more of an ask to add to a tutorial than a feature request as I believe this might already doable today.
When looking at the FeatureSpace tutorials it assumes that you create one output per f…
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Would it be possible to expand the use of the h-statistic to other algorithms? Or is there some inherent quality that makes GBMs ideal for h-statistic calculation?
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Microsoft pre-released the Explainable Boosting Machine 2 weeks ago:
https://github.com/microsoft/interpret
It has very promising performance profile
| Dataset/AUROC | Domain | Logistic Regr…
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Re: https://github.com/Trusted-AI/adversarial-robustness-toolbox/blob/main/art/metrics/metrics.py, could you please add examples of computing different adversarial robustness metrics, e.g., empirical…
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**Describe the issue**
It is a miss in your benchmarking. I think you should look at the "time-series-bakeoff" for others like it.
DTW is a pain, and very well known and well used method.
The …
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### Is there an existing issue for this?
- [X] I have searched the existing issues
### Feature Description
Gradient Boosted Regression Trees (GBRT) is an ensemble learning technique used for regres…
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It may be possible to use non gradient-based techniques like `fmin_powell`. See (http://www.scipy-lectures.org/advanced/mathematical_optimization/index.html#a-shooting-method-the-powell-algorithm)
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```
There are two issues:
1) setting the seed does not ensure reproducibility of the model
2) when no predictors are used in any splits, the predicted values are somewhat
inconsistent; sometimes NA …
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```
There are two issues:
1) setting the seed does not ensure reproducibility of the model
2) when no predictors are used in any splits, the predicted values are somewhat
inconsistent; sometimes NA …