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Found 5 papers, 2 papers with code
Predictive Churn with the Set of Good Models
And we characterize expected churn over model updates via the Rashomon set, pairing our analysis with empirical results on real-world datasets -- showing how our approach can be used to better anticipate, reduce, and avoid churn in consumer-facing applications.
Rashomon Capacity: A Metric for Predictive Multiplicity in Classification
Predictive multiplicity occurs when classification models with statistically indistinguishable performances assign conflicting predictions to individual samples.
Obfuscation via Information Density Estimation
The core of this mechanism relies on a data-driven estimate of the trimmed information density for which we propose a novel estimator, named the trimmed information density estimator (TIDE).
Predictive Multiplicity in Classification
We apply our tools to measure predictive multiplicity in recidivism prediction problems.
Optimized Score Transformation for Consistent Fair Classification
We derive a closed-form expression for the optimal transformed scores and a convex optimization problem for the transformation parameters.
