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 LinearRegressionIn [15]: from sklearn.datasets import load_boston dataset = load_boston()In [16]: samples , label, feature_names = dataset.data, ...
