The question comes from when I was wondering about the cross-validation, finding out the best algorithm.

Then I got the question like if this model did a better job than the other, can the combination of two on different subpopulation be a better algorithm. Let say the model of KNN did a pretty job predict these types of people on these attributes and did a bad job on a complex outcome due to the large dimension. we use KNN for the subset that is small then the rest used another better method may be logistic regression.

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  • $\begingroup$ Why should this be a problem? Assuming that you're not overfitting to the training data, why not? $\endgroup$ – Tim Jan 10 '19 at 15:34
  • $\begingroup$ You are totally out the point, I did not ask to solve the problem, I ask if it could and may it be a better solution. $\endgroup$ – EconBoy Jan 10 '19 at 15:46

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