{"library":"betacal","type":"library","category":null,"description":"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.","language":"python","status":"active","version":"1.1.0","tags":["calibration","machine-learning","scikit-learn","probability-calibration","binary-classification"],"last_verified":"Sat May 23","install":[{"cmd":"pip install betacal","imports":["from betacal import BetaCalibration"]}],"homepage":"https://betacal.github.io/","github":"https://github.com/betacal/python","docs":null,"changelog":null,"pypi":"https://pypi.org/project/betacal/","npm":null,"openapi_spec":null,"status_page":null,"smithery":null,"compatibility":{"summary":{"python_range":"3.10–3.9","success_rate":50,"avg_install_s":9.4,"avg_import_s":3.6,"wheel_type":"wheel"},"url":"https://checklist.day/v1/registry/betacal/compatibility"}}