Output Layer Quick Reference
Recall common output-layer patterns for regression, binary, multi-class, and multi-label tasks.
Softmax or sigmoid? Most common fork Ask: can two labels be true for one example? Continuous value prediction, like house price or temperature. Name the head pattern. Regression head Often a linear output with a regression loss such as MSE or MAE, depending on the objective. The labels are zero and one, so mean squared error should be fine for classification. You are reviewing a binary classifier implementation. Your line For classification, use a loss that matches probabilities, such as binary cross-entropy for a sigmoid binary output. Numeric label storage does not define the learning objective. The response separates data…
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