linrmll.py

import matplotlib.pyplot as plt
import numpy as np
from sklearn import datasets,linear_model
from sklearn.metrics import mean_squared_error
diabetes=datasets.load_diabetes()
diabetes_X=diabetes.data[:,np.newaxis,2]
diabetes_X_train=diabetes_X[:-30]
diabetes_X_test=diabetes_X[-30:]
diabetes_y_train=diabetes.target[:-30]
diabetes_y_test=diabetes.target[-30:]
model=linear_model.LinearRegression()
model.fit(diabetes_X_train,diabetes_y_train)
diabetes_y_predicted=model.predict(diabetes_X_test)
print("mse is:",mean_squared_error(diabetes_y_test,diabetes_y_predicted))
print("weights:",model.coef_)
print("intercept:",model.intercept_)
plt.scatter(diabetes_X_test,diabetes_y_test)
plt.plot(diabetes_X_test,diabetes_y_predicted)
plt.show()