scikit_learn_linear_model_demo.py

import numpy as np
from sklearn.linear_model import LinearRegression
import matplotlib.pyplot as plt
from matplotlib.font_manager import FontProperties

x = [[1],[2],[3],[4],[5],[6]]
y = [[1],[2.1],[2.9],[4.2],[5.1],[5.8]]
model = LinearRegression()
model.fit(x, y)
x2 = [[0], [2.5], [5.3], [9.1]]
y2 = model.predict(x2)

plt.figure()
plt.title('linear sample')
plt.xlabel('x')
plt.ylabel('y')
plt.axis([0, 10, 0, 10])
plt.grid(True)
plt.plot(x, y, 'k.')
plt.plot(x2, y2, 'g-')
plt.show()
print np.var([1,2,3,4,5,6], ddof=1)
print np.cov([1,2,3,4,5,6], [1,2.1,2.9,4.2,5.1,5.8])[0][1]