python - Picking n_neighbors for KNeighborsClassifier -

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simple question couldn't find answer anywhere online. based on data, how pick number use n_neighbors? or best use default of 5? data set working uses 13 values predict target.

you should try different parameters , evaluate them via cross validation. sklearn has class that: gridsearchcv:

g = gridsearchcv(kneighborsclassifier(), { "n_neighbors" : [5, 7, 11, 13, 17] }) g.fit(x, y)

it's easy customize scoring function , (most importantly) run evaluations in parallel.


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