Materials for STAT 991: Topics In Modern Statistical Learning (UPenn, 2022 Spring) - uncertainty quantification, conformal prediction, calibration, etc
-
Updated
May 17, 2024
Materials for STAT 991: Topics In Modern Statistical Learning (UPenn, 2022 Spring) - uncertainty quantification, conformal prediction, calibration, etc
Example on task completion times stressing the importance of distribution-free intervals, as well as .py file containing code to calculate such intervals.
Python library for tolerance intervals. Derived from: Derek S. Young (2010). tolerance: An R Package for Estimating Tolerance Intervals. Journal of Statistical Software, 36(5), 1-39. URL http://www.jstatsoft.org/v36/i05/.
calculateur de correcteurs dynamiques
Add a description, image, and links to the tolerance-intervals topic page so that developers can more easily learn about it.
To associate your repository with the tolerance-intervals topic, visit your repo's landing page and select "manage topics."