mlessentials/Chapter08/Examples/setting_hyperparameters.ipynb

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from sklearn import neighbors

# initialize with default hyperparameters
knn = neighbors.KNeighborsClassifier()

# examine the defaults
print(knn.get_params())

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# initialize with k = 15 and all other hyperparameters as default 
knn = neighbors.KNeighborsClassifier(n_neighbors=15)

# examine
print(knn.get_params())

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# initialize with k = 15, weights = distance and all other hyperparameters as default 
knn = neighbors.KNeighborsClassifier(n_neighbors=15, weights='distance')

# examine
print(knn.get_params())