What is Your Metric Telling You? Evaluating Classifier Calibration under Different Definitions of Reliability
Abstract
An argument for uncertainty in machine learned models. This work: Evaluating classifiers for context-specific calibration. How do you evaluate your classifier for it's ability to accurately express uncertainty? First, you need to define how to interpret the confidence outputs of classifiers.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jan 01, 2021
- Accession Number
- AD1150239
Entities
People
- Eric T. Heim
Organizations
- Carnegie Mellon University