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See https://ecoevorxiv.org/repository/view/8041/
This is probably something @gottacatchenall and I can get started on, and it's a really neat way to show uncertainty coming from the model itself
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hi @mitchelloharawild -
Related to a similar expansion in the `forecast` framework, [conformalForecast](https://github.com/xqnwang/conformalForecast), is there any chance conformal methods will b…
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Conformal predictions could be a valuable addition to darts.
It would require some brain storming/planning of how (or if) we can integrate this into our API / extend the API.
Some links:
- htt…
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**Is your feature request related to a problem? Please describe.**
> Despite attractive theoretical guarantees and practical successes, Predictive Interval (PI) given by Conformal Prediction (CP) m…
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# Enhancement: Add Uncertainty Metric to Naive Bayes Classifier
## Description
To improve the reliability and interpretability of our Naive Bayes classifier, we should implement an uncertainty met…
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### Module
Other
### Contact Details
_No response_
### Feature Request
Do you think that your library can be used for semantic segmentation (pixel-wise prediction with multi classes) ?
Do you p…
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**Describe the bug**
I am trying to create a working example of using ConformalIntervals for time series forecasting. I am using a ML regressor within make_reduction(LGB) to train my model. I run i…
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**Is your feature request related to a problem? Please describe.**
Conformal Prediction is a powerful uncertainty quantification framework that can benefit multiple stages of Twitter algorithm
**D…
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**Describe the feature request you'd like**
Include `SCPI` as a second, alternative method within the `MapieTimeSeriesRegressor` class alongside the existing `EnbPI` method.
**Why is this benefici…
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### 🚀 The feature, motivation and pitch
I propose the addition of a conformal prediction framework to the PyTorch library. This framework would include the implementation of split conformal predictio…