Calibrating a classification system consists in transforming the output scores, which somehow state the confidence of the classifier regarding the predicted output, into proper probability estimates. Having a well-calibrated classifier has a non-negligible impact on many real-world applications, for example decision making systems synthesis for anomaly detection/fault prediction. In such industrial scenarios, risk assessment is certainly related to costs which must be covered. In this paper we review three state-of-the-art calibration techniques (Platt’s Scaling, Isotonic Regression and SplineCalib) and we propose three lightweight procedures based on a plain fitting of the reliability diagram. Computational results show that the three proposed techniques have comparable performances with respect to the three state-of-the-art approaches.
Calibration techniques for binary classification problems. A comparative analysis / Martino, Alessio.; De Santis, Enrico.; Baldini, Luca; Rizzi, Antonello. - (2019), pp. 487-495. (Intervento presentato al convegno 11th International Joint Conference on Computational Intelligence, IJCCI 2019 tenutosi a Vienna; Austria) [10.5220/0008165504870495].
Calibration techniques for binary classification problems. A comparative analysis
Martino, Alessio.;De Santis, Enrico.;BALDINI, LUCA;Rizzi, Antonello
2019
Abstract
Calibrating a classification system consists in transforming the output scores, which somehow state the confidence of the classifier regarding the predicted output, into proper probability estimates. Having a well-calibrated classifier has a non-negligible impact on many real-world applications, for example decision making systems synthesis for anomaly detection/fault prediction. In such industrial scenarios, risk assessment is certainly related to costs which must be covered. In this paper we review three state-of-the-art calibration techniques (Platt’s Scaling, Isotonic Regression and SplineCalib) and we propose three lightweight procedures based on a plain fitting of the reliability diagram. Computational results show that the three proposed techniques have comparable performances with respect to the three state-of-the-art approaches.File | Dimensione | Formato | |
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