Python KNN

# -*- coding: utf-8 -*-

import numpy

from sklearn import datasets

#引入数据集

iris = datasets.load_iris()

iris

#查看数据的规模

iris.data.shape

#查看训练目标的总类

numpy.unique(iris.target)

from sklearn.model_selection import train_test_split

data_train, data_test, target_train, target_test = train_test_split(

iris.data,

iris.target,

test_size=0.3

)

data_train.shape

data_test.shape

target_train.shape

target_test.shape

from sklearn import neighbors

knnModel = neighbors.KNeighborsClassifier(n_neighbors=3)

knnModel.fit(data_train, target_train)

knnModel.score(data_test, target_test)

from sklearn.model_selection import cross_val_score

cross_val_score(

knnModel,

iris.data, iris.target, cv=5

)

#使用模型进行预测

knnModel.predict([[0.1, 0.2, 0.3, 0.4]])