机器学习—knn实现鸢尾花分类（利用sklearn）

import sklearn.datasets as skdata

import matplotlib.pyplot as plt

import seaborn as sns

import pandas as pd

import sklearn.model_selection as skmodel

import sklearn.neighbors as skneighbors

import sklearn.preprocessing as skprep

iris_data = skdata.load_iris()

iris_data

type(iris_data)

dir(iris_data)

iris_data.feature_names

iris_df = pd.DataFrame(iris_data['data'],columns = ['sepal length (cm)','sepal width (cm)','petal length (cm)','petal width (cm)'])

iris_df['Species'] = iris_data.target

iris_df

sns.relplot(x='sepal width (cm)', y='petal length (cm)', data=iris_df, hue='Species')

x_train,x_test,y_train,y_test = skmodel.train_test_split(iris_data.data,iris_data.target,test_size = 0.2)

x_train,x_test,y_train,y_test

knn_model = skneighbors.KNeighborsClassifier(n_neighbors = 7)

knn_model.fit(x_train,y_train)

y_predict = knn_model.predict(x_test)

y_predict == y_test

score = knn_model.score(x_test, y_test)

score