Calibration is one of the most important concepts in machine learning. It tells us how much we can trust a model prediction, especially in classification models.
Having a good grasp of calibration is a necessity for the meaningful interpretation of numerical outputs of machine learning classifiers. In this article, we'll discuss the theory behind machine learning model calibration and its importance through some simple real-life examples.
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