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Category "mean-square-error"

Comparing MSE loss and cross-entropy loss in terms of convergence

For a very simple classification problem where I have a target vector [0,0,0,....0] and a prediction vector [0,0.1,0.2,....1] would cross-entropy loss converge

Why doesn't mean square error work in case of angular data?

Suppose, the following is a dataset for solving a regression problem: H -9.118 5.488 5.166 4.852 5.164 4.943 8.103 -9.152 7.470 6.452 6.069 6

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