Scikit-Learn -2

Scikit-Learn

目录

from sklearn import datasets
from sklearn.linear_model import LinearRegression
#加载Boston数据
loaded_data = datasets.load_boston()
data_X = loaded_data.data
data_y = loaded_data.target
#线性回归模型
model = LinearRegression()
model.fit(data_X,data_y)
#预测10个数据
print(model.predict(data_X[:10,:]))
print(data_y[:10])


print(model.coef_)
print(model.intercept_)

print(model.get_params())
print(model.score(data_X,data_y))#R^2 coefficient of determination

coef 、intercept

-官网的描述

get_params

-得到默认的参数

自己做一个数据集

都是datasets.make

from sklearn import datasets
import matplotlib.pyplot as plt
#100个点 具体的以后再说
X,y = datasets.make_regression(n_samples=100,n_features=1,n_targets=1,noise=10)
plt.scatter(X,y)
plt.show()

分别显示noise = 1，5，10