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Why do we not use a mean-square-error-like error for logistic regression?
The gradient of such loss function can cause numerical instability
We cannot find find the gradient of such loss function
The mean-square error loss can lead to poor convergence when the predictions are far from the true labels due to gradients being extremely small.
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