-
Thanks for a fantastic series about conformal prediction. I am working on a model that outputs predictions for 100s-1000s of variables. Is it possible to use conformal predictors in that case?
Doe…
vitkl updated
8 months ago
-
**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…
-
### Describe the workflow you want to enable
Conformal prediction (CP) is a statistical technique for producing prediction sets without assumptions on the predictive algorithm (often a machine learni…
-
I often need to perform active learning in the context of multioutput regression. I thus need a measure of uncertainty for my regressor. However, MapieRegressor is not compatible with MultiOutputRegre…
-
Conformal Quantile Regression was introduced in [Romano, Patterson & Candès](https://arxiv.org/abs/1905.03222) and is a variant of quantile regression which calibrates the prediction intervals, yieldi…
-
Add nonconfomity score and prediction set functions for conformal multivariate regression in their respective modules.
-
Thank you for your library!
Is there any easy way to save the fitted and calibrated conformal predictors for re-use? I'd like to make conformal predictions in an online setting.
I tried just …
-
### Contact Details
geethen.singh@gmail.com
### Dataset description
Using a modern uncertainty quantification method, conformal prediction, we have quantified the uncertainty for the first non-null…
-
@yromano In conformal prediction, the regression algorithm must treat the data exchangeably. I want to know whether CQR must treat the data exchangeably.
-
It would be interesting to be able to add bootstrapping functionnality from residuals of a model of the time series, this would help :
1. to compute prediction intervals when the method doesn't su…