在Python中将KNN从小型监督数据集应用到大型无监督数据集

from sklearn.neighbors import KNeighborsClassifier
from sklearn.neighbors import KNeighborsRegressor
from sklearn.model_selection import train_test_split
from sklearn.metrics import accuracy_score, mean_squared_error

X = [[1, 2], [3, 4], [5, 6], [7, 8]]
y = [0, 0, 1, 1]

X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)

k = 3  # 设置K值
knn_classifier = KNeighborsClassifier(n_neighbors=k)
knn_classifier.fit(X_train, y_train)

knn_regressor = KNeighborsRegressor(n_neighbors=k)
knn_regressor.fit(X_train, y_train)

y_pred_classifier = knn_classifier.predict(X_test)
accuracy = accuracy_score(y_test, y_pred_classifier)
print("分类准确率：", accuracy)

y_pred_regressor = knn_regressor.predict(X_test)
mse = mean_squared_error(y_test, y_pred_regressor)
print("回归均方误差：", mse)