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What explains the apparent 'mirroring' of the graphs on the RHS, The model starts untrained and no better than random guessing (the baseline). As the training progresses, the model does better than random guessing on the training data, but does worse than initially on the validation data. The decrease in performance is because the data it is being trained ...


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Sklearn has digit dataset with images of size $8 \times 8$: Classes 10 Samples per class ~180 Samples total 1797 Dimensionality 64 Features integers 0-16


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