Using linear regression to model housing prices

In the section, we will perform multivariate linear regression for the same dataset. In contrast to the previous section, we will use the sklearn library to show you several ways of performing linear regression models. Before we start the linear regression model, we will trim the dataset proportionally from both sides by using the trimboth() method. By doing this, we will cut off the outliers:

In [14]: import numpy as np
         import pandas as pd
         from scipy import stats
         from sklearn.cross_validation import train_test_split
         from sklearn.linear_model import LinearRegression
In [15]: from sklearn.datasets import load_boston
         dataset = load_boston()
In [16]: samples , label, feature_names = dataset.data, dataset.target, dataset.feature_names
In [17]: samples_trim = stats.trimboth(samples, 0.1)
         label_trim...