How the five tribes of ML learn programs: Connectionists: Differentiable programming Bayesians: Probabilistic programming Symbolists: Inductive logic programming Evolutionaries: Genetic programming Analogizers: Case-based reasoning
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Is genetic programming ML? Not sure there is much learning going on.
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Thank you. I find it difficult to put in the same class as the others. Where is a model that can be generalised to a different input? Is it synthesised in the final winning genes that can be used to kickstart another optimisation? Doesn't seem the same as NNs.
Kiitos. Käytämme tätä aikajanasi parantamiseen. KumoaKumoa
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