使用scikit-learn中的KNN包实现对鸢尾花数据集的预测

from sklearn.datasets import load_iris
from sklearn.model_selection import train_test_split
from sklearn.neighbors import KNeighborsClassifier
from sklearn.preprocessing import StandardScaler

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, random_state=42)

transfer = StandardScaler()

ret_train_data = transfer.fit_transform(X_train)
ret_test_data = transfer.fit_transform(X_test)

k = 5
knn = KNeighborsClassifier(n_neighbors=k)
knn.fit(X_train, y_train)

knn.fit(ret_train_data, y_train)

y_pre = knn.predict(ret_test_data)
print("预测值是 : ", y_pre)
print("真实值是 : ", y_test)
score = knn.score(ret_test_data, y_test)
print("预测准确率是 : ", score)