请使用sklearn的KNN算法(k选择3),对给定的测试数据X_test进行分类
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X_train = [[1, 180, 85], [1, 180, 86], [1, 180, 90], [1, 180, 100],
[1, 185, 120], [1, 175, 80], [1, 175, 60], [1, 170, 60],
[1, 175, 90], [1, 175, 100], [1, 185, 90], [1, 185, 80]]
y_train = ['稍胖', '稍胖', '稍胖', '过胖','太胖', '正常', '偏瘦', '正常', '过胖', '太胖', '正常', '偏瘦']
X_test = [[1, 180, 70], [1, 160, 90], [1, 170, 85]]
#导入模型
from sklearn.neighbors import KNeighborsClassifier
#创建实例
knn = KNeighborsClassifier(3)
#模型训练
knn.fit(X_train, y_train)
#模型预测
result=knn.predict(X_test)
print(result)
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