Guide for Linear Regression using Python – Part 2 This blog is the continuation of guide for linear regression using Python from this post. There must be no correlation among independent variables. Multicollinearity is the presence of correlation in independent variables. If variables are correlated, it becomes extremely difficult for the model to determine the true effect of X on…

# Tag: Regression

## Guide for Linear Regression using Python – Part 1

Regression is the first algorithm we need to master if we are aspiring to become a data scientist. It is one of the easiest algorithms to learn yet requires understanding and effort to get to the master it. In this blog is a guide for linear regression using Python. It will focus on linear and multiple regression. We will learn the…

## Regression in scikit-learn

We will compare several regression methods by using the same dataset. We will try to predict the price of a house as a function of its attributes. In [6]: import numpy as np import matplotlib.pyplot as plt %pylab inline Populating the interactive namespace from numpy and matplotlib Import the Boston House Pricing Dataset In [9]: from sklearn.datasets import load_boston boston = load_boston()…