Boston House Price with Scikit-Learn

Boston House Price with Scikit-Learn

Data Description

>>> from sklearn.datasets import load_boston

>>> boston = load_boston()
>>> x, y = boston.data, boston.target
>>> print(x.shape)
(506, 13)
>>> print(y.shape)
(506,)

Regression with Linear Regression Model

# encoding:utf8

from sklearn.datasets import load_boston
from sklearn.model_selection import train_test_split
from sklearn.linear_model import LinearRegression
from sklearn.metrics import mean_squared_error, mean_absolute_error


if __name__ == '__main__':
    boston = load_boston()
    x, y = boston.data, boston.target
    x_train, x_test, y_train, y_test = train_test_split(x, y, test_size=0.2)

    model = LinearRegression()
    model.fit(x_train, y_train)
    y_pred = model.predict(x_test)

    print("mse: %f" % mean_squared_error(y_test, y_pred))
    print("mae: %f" % mean_absolute_error(y_test, y_pred))