%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
from sklearn import datasets

x = np.random.rand(50)
y = 7 * x - 3 + np.random.rand(50)
plt.scatter(x, y);

from sklearn import linear_model
linreg = linear_model.LinearRegression()
linreg.fit(x[:, np.newaxis], y)
xfit = np.linspace(0, 1, 10)
yfit = linreg.predict(xfit[:, np.newaxis])
plt.scatter(x, y)
plt.plot(xfit, yfit);

print("Pente: ", linreg.coef_[0])
print("Ordonné à l'origine", linreg.intercept_)

Diabètes = datasets.load_diabetes()