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Perceptron without a step or sigmoid threshold

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Reference no: EM131549342

As mentioned in class, a perceptron without a step or sigmoid threshold is simply a linear function, and therefore the learning is the same as linear regression. Is this still true for multi-layer networks built out of the same type of (non-thresholding) perceptrons? Explain specifically why or why not.

Reference no: EM131549342

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