from sklearn.model_selection import cross_val_score
# 10-fold cross-validation with K=5 for KNN (the n_neighbors parameter)
knn = KNeighborsClassifier(n_neighbors=5)
scores = cross_val_score(knn, X, y, cv=10, scoring='accuracy')
print(scores)

# Output

[1.         0.93333333 1.         1.         0.86666667 0.93333333
 0.93333333 1.         1.         1.        ]

# use average accuracy as an estimate of out-of-sample accuracy
print(scores.mean())
# Output

0.9666666666666668