from sklearn.neighbors import KNeighborsClassifier from sklearn.model_selection import train_test_split import numpy as np from sklearn import datasets from sklearn import metrics iris=datasets.load_iris() iris_x=iris.data iris_y=iris.target # print(iris_x) X_train, X_test, y_train, y_test = train_test_split(iris_x, iris_y, test_size=0.2, random_state=42) #定义模型 knn=KNeighborsClassifier(n_neighbors=3) knn.fit(X_train,y_train) # knn.fit(X_train,y_train.ravel()) #预测 y_pred_on_train=knn.predict(X_test) #输出 print(y_pred_on_train) print("------------") print(y_test) acc=metrics.accuracy_score(y_test,y_pred_on_train) print(acc)
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转载自blog.csdn.net/qq_39622065/article/details/80213191
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