KNN-学习笔记

仅供学习使用

练习1

# coding:utf-8

# 2019/10/16 16:49

# huihui

# ref:

import numpy as np

from sklearn import datasets

from sklearn.model_selection import train_test_split

from sklearn.neighbors import KNeighborsClassifier

iris = datasets.load_iris()

X = iris.data

y = iris.target

print(X, y)

X_train, X_test, y_train, y_test = train_test_split(X, y,random_state=2003)

clf = KNeighborsClassifier(n_neighbors=3)

clf.fit(X_train, y_train)

correct = np.count_nonzero((clf.predict(X_test) == y_test) == True)

print("准确率：%.3f" % (correct / len(X_test)))

巴特西

KNN-学习笔记

练习1

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