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by erichahn
1911 days ago
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I mean yes, there is parametric ML (maximum likelihood, MAP, GMMs, ...) and there is non-parametric ML (everything neural network, SVM, GBM, random forrests, ...). I'd argue that the latter had bigger success in the past since the prior on the data distribution is usually wrong in real life. Think about a prior for image data distributions or the same in nlp. Forget about it. |
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