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Last active March 11, 2024 17:22
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About the miscalibration of logistic regression models
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Miscalibration_of_logistic_regression_models.ipynb
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@lorentzenchr
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Note that the model is severly miscalibrated despite the balance property. This property only informs us about marginal calibration, not about auto-calibration.

This is not the whole story. The balance property just holds for the design matrix of the logistic regression. If the design matrix is badly chosen, then the balance property is just (very) weak. For instance, if only random features without correlation to the target are chosen, the balance property reduces to the marginal (the conditioning drops out), which is weak.
On the other hand, for a "correct" design matrix, the balance property is stronger than auto-calibration.

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