Over a million developers have joined DZone.

Linear Regression Using Python scikit-learn

DZone's Guide to

Linear Regression Using Python scikit-learn

Let's say you have some people's height and weight data. Can you use it to predict other people's weight? Find out using Python scikit-learn.

· AI Zone ·
Free Resource

Did you know that 50- 80% of your enterprise business processes can be automated with AssistEdge?  Identify processes, deploy bots and scale effortlessly with AssistEdge.

In this article, I am going to explain how to use scikit-learn/sk-learn, a machine learning package in Python, to do linear regression for a set of data points.

Below is a video tutorial on this:

 I am not going to explain training data, testing data, and model evaluation concepts here, but they are important.

We know that the equation of a line is given by y=mx+b, where m is the slope and b is the intercept.

Our goal is to find the best values of slope (m) and intercept (b) to fit our data.

Linear regression uses the ordinary least squares method to fit our data points.

import statement:

from sklearn import linear_model

I have the height and weight data of some people. Let's use this data to do linear regression and try to predict the weight of other people.

weight=[  42 ,  44 , 49, 55  , 53  , 58   , 60  , 64  ,  66 ,  69]

print("height weight")
for row in zip(height, weight):


height weight
4.0 -> 42
4.5 -> 44
5.0 -> 49
5.2 -> 55
5.4 -> 53
5.8 -> 58
6.1 -> 60
6.2 -> 64
6.4 -> 66
6.8 -> 69

import statement to plot graph using matplotlib:

import matplotlib.pyplot as plt

Plotting the height and weight data:



Image title

Declaring the linear regression function and call the fit method to learn from data:


Slope and intercept:

print("slope=",m, "intercept=",b)


slope= 10.1936218679 intercept= -0.4726651480
Using the values of slope and intercept to construct the line to fit our data points:
predicted_values = [reg.coef_ * i + reg.intercept_ for i in height]
plt.plot(height, predicted_values, 'b')
Image title

And that's it!

Linear regression in python scikit learn | Quick KT

Consuming AI in byte sized applications is the best way to transform digitally. #BuiltOnAI, EdgeVerve’s business application, provides you with everything you need to plug & play AI into your enterprise.  Learn more.

machine learning ,linear regression ,python ,scikit-learn ,sklearn ,ai ,predictive analytics ,tutorial

Published at DZone with permission of

Opinions expressed by DZone contributors are their own.

{{ parent.title || parent.header.title}}

{{ parent.tldr }}

{{ parent.urlSource.name }}