Comments (3)
They are "pre-absoluted" and pre-sorted for split inference and only pre-sorted for quantile inference.
For the quantile method, I was working off of Ryan Tibshirani's notes (page 13 section 4.2), which does not use the absolute value (and probably doesn't need to since it operated in a completely different way).
If it helps, I did do a pretty thorough simulation of these functions to check their coverage. Not that there are no errors in the code, but the current version does seem to do what it is intended to do (statistically, at least).
from probably.
@mdancho84 that seems consistent with what Angelopoulos, Bates do in Gentle Introduction to Conformal Prediction...
Same issue looks like it is in predict.int_conformal_quantile()
:
probably/R/conformal_infer_quantile.R
Line 129 in 1d4b4c1
from probably.
They are "pre-absoluted" and pre-sorted for split inference and only pre-sorted for quantile inference.
Ahh, I see now, thanks. (For quantile based method, the Angelopoulos & Bates paper I referenced also just sorts and does not take absolutes -- consistent with your implementation / Tibshirani.)
from probably.
Related Issues (20)
- use of native pipe incompatible with documented R version HOT 1
- Problem with names of columns like `probability_*` HOT 1
- augment methods for conformal prediction
- make a note about extrapolation with conformal quantile regression
- Add hex
- Modeltime Integration: Conformal Prediction Intervals for Time Series Forecasting HOT 1
- `cal_estimate_*()` with factor variable passed to `.by` fails
- Upkeep for probably (2023) HOT 1
- Error in `cal_plot_breaks()` HOT 3
- Generalize `int_conformal_quantile()`
- Release probably 1.0.2
- unused helper in source code
- `.by` argument works incorrectly for factor level groups.
- int_conformal_cv doesn't work with group_vfold_cv HOT 1
- data using in calibration validate functions
- Error in cal_plot_breaks()
- Updating predicted classes after calibrating probabilities doesn't work for non-syntactic levels
- Inconsistent appearance of `distance` metric in `threshold_perf()` HOT 1
- Implement Venn-ABERS predictor for classification
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from probably.