How to determine the k in kNN

Asked Aug 15 '18 at 04:52

Active Aug 15 '18 at 13:51

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I'm looking to use the k-Nearest Neighbors (kNN) algorithm. What are the possible methods for determining the best K? From what I have read, looking at many different values(say 10-100) should work, but that's a big range.

How can I reduce the range of possible K's I should test?

edited Aug 15 '18 at 13:51

Stephen Rauch

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asked Aug 15 '18 at 04:52

m k

Don't you mean k? – DuttaA Aug 15 '18 at 05:58
You could use GridSerchCV, RandomSearchCV, or BayesianOptimization to find the best hyperparameters if you are using Python – ebrahimi Aug 15 '18 at 06:13
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The K in kNN is a hyperparameter. You should look for: how to optimize a hyperparameter. – Bruno Lubascher Aug 15 '18 at 08:03
how do you tune any ML algorithm? Do a grid search on a small subset of the data in question. – Mohammad Athar Aug 15 '18 at 14:25
ebrahimi and Mohammad Athar those both sound like answers not comments. If you post it as an answer then others can vote it up in agreement – kbrose Aug 15 '18 at 16:14

How to determine the k in kNN

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