python使用KNN算法实现鸢尾花数据的分类

好的，这是一个很典型的机器学习问题。以下是实现步骤：

1. 导入所需的库和数据集：

from sklearn.datasets import load_iris
from sklearn.model_selection import train_test_split
from sklearn.neighbors import KNeighborsClassifier
from sklearn.metrics import accuracy_score

iris = load_iris()
X = iris.data
y = iris.target

2. 分割数据集，将数据集分为训练集和测试集：

X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3)

3. 构建KNN分类器，并对训练集进行训练：

knn = KNeighborsClassifier(n_neighbors=3)
knn.fit(X_train, y_train)

4. 对测试集进行预测：

y_pred = knn.predict(X_test)

5. 计算模型的准确率：

accuracy = accuracy_score(y_test, y_pred)
print("Accuracy:", accuracy)

完整代码如下：

from sklearn.datasets import load_iris
from sklearn.model_selection import train_test_split
from sklearn.neighbors import KNeighborsClassifier
from sklearn.metrics import accuracy_score

iris = load_iris()
X = iris.data
y = iris.target

X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3)

knn = KNeighborsClassifier(n_neighbors=3)
knn.fit(X_train, y_train)

y_pred = knn.predict(X_test)

accuracy = accuracy_score(y_test, y_pred)
print("Accuracy:", accuracy)

希望对你有帮助！