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I am looking for classification/ regression methods that could be considered "white box" models, meaning they have some degree of interpretability or "can be explained".

My dataset has 16 dimensions and 10 classes, I thought about "Support vector machines" and "K-nearest neighbors", but do both of them still be interpretable at this number of dimensions and classes?

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  • $\begingroup$ What do you mean by "interpretable?" What type of information would you like to know from your model's predictions? $\endgroup$ – tchainzzz Mar 29 at 20:55

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