What is “generalization” ?

I’ve been pondering this question for a while now. If x is a Cat, then x + dx is everything that can be still recognized as a Cat… the bigger dx the more “general” the inference. dx has to have a dx_Max, if dx > dx_Max then x+dx cannot be recognized as a Cat. As far as I can tell this is how “Deep Learning” does generalization and I believe this is how we do generalization too.. How am I trying to do generalization ? The same basically but the source of errors (what changes dx value) are multiple… In the end, whatever signal activates a neuron N, is a Cat…

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