莫烦python教程学习笔记——使用波士顿数据集、生成用于回归的数据集

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"""

Please note, this code is only for python 3+. If you are using python 2+, please modify the code accordingly.

"""

from __future__ import print_function

from sklearn import datasets

from sklearn.linear_model import LinearRegression

import matplotlib.pyplot as plt

loaded_data = datasets.load_boston()

data_X = loaded_data.data

data_y = loaded_data.target


#用线性回归模型预测波士顿房价

model = LinearRegression()

model.fit(data_X, data_y)

print(model.predict(data_X[:4, :]))

print(data_y[:4])


#利用python自带的工具，生成用于回归的数据集，可以设置参数决定是否加入噪声等设置

X, y = datasets.make_regression(n_samples=100, n_features=1, n_targets=1, noise=10)

plt.scatter(X, y)

plt.show()