Beta Calibration

BetaCal provides a Python implementation of Beta Calibration, a method for calibrating predicted probabilities from binary classifiers. It offers a well-founded and easily implemented improvement over traditional logistic calibration, particularly effective when classifiers suffer from scores that tend too much to the extremes or when an already well-calibrated model might be uncalibrated by logistic methods. The current version is 1.1.0, last released in April 2021. While functional and widely cited, the package's release cadence is slow, suggesting a maintenance rather than active development phase.