Approximating hidden function using scikit-learn linear regression model

linear_regression.py

import numpy as np
from sklearn.linear_model import LinearRegression

def f(x):
    return 1 + 0.87*x[0] + 0.34*x[1] + 0.5*x[2]

X = np.random.random((2000, 3)) * 100
y = [f(x) for x in X]

lm = LinearRegression()
lm.fit(X, y)
x = [[2, -1, 5]];
print(lm.predict(x), f(x[0]))