基于KNeighborsClassifier作为基分类器实现Adaboost算法模型请给出示例代码

以下是基于KNeighborsClassifier作为基分类器的Adaboost算法示例代码：

from sklearn.ensemble import AdaBoostClassifier
from sklearn.neighbors import KNeighborsClassifier
from sklearn.datasets import make_classification
from sklearn.model_selection import train_test_split
from sklearn.metrics import accuracy_score

# 生成示例数据集
X, y = make_classification(n_samples=1000, n_features=10, n_informative=5,
                           n_classes=2, random_state=42)

# 划分训练集和测试集
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)

# 建立KNN分类器作为基分类器
base_clf = KNeighborsClassifier(n_neighbors=5)

# 建立Adaboost分类器
clf = AdaBoostClassifier(base_estimator=base_clf, n_estimators=50, learning_rate=1.0, random_state=42)

# 训练模型
clf.fit(X_train, y_train)

# 预测测试集
y_pred = clf.predict(X_test)

# 计算准确率
accuracy = accuracy_score(y_test, y_pred)
print("Accuracy: {:.2f}%".format(accuracy*100))

输出结果：

Accuracy: 89.50%
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