Example code for the HuberEstimator

huber.py

import numpy as np

from sklearn.datasets import make_regression, load_boston
from sklearn.linear_model import HuberRegressor
from sklearn.metrics import mean_squared_error
from sklearn.preprocessing import StandardScaler
from sklearn.grid_search import GridSearchCV
from sklearn.utils.estimator_checks import NotAnArray, _boston_subset

boston = load_boston()
X, y = boston.data, boston.target
X = StandardScaler().fit_transform(X)
y = StandardScaler().fit_transform(y)

huber = HuberRegressor(fit_intercept=True)
huber.fit(X, y)
y_pred = huber.predict(X)
print(mean_squared_error(y, y_pred))