Skip to content

Linear regression is a statistical approach for modelling relationship between a dependent variable with a given set of independent variable

Notifications You must be signed in to change notification settings

shubham141/Regression_in_Python

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

3 Commits
 
 
 
 
 
 

Repository files navigation

Regression

**Linear Regression (Python Implementation) This article discusses the basics of linear regression and its implementation in Python programming language.

**Linear regression is a statistical approach for modelling relationship between a dependent variable with a given set of independent variables.

Note: In this article, we refer dependent variables as response and independent variables as features for simplicity.

In order to provide a basic understanding of linear regression, we start with the most basic version of linear regression, i.e. Simple linear regression.

Simple Linear Regression Simple linear regression is an approach for predicting a response using a single feature.

It is assumed that the two variables are linearly related. Hence, we try to find a linear function that predicts the response value(y) as accurately as possible as a function of the feature or independent variable(x).

About

Linear regression is a statistical approach for modelling relationship between a dependent variable with a given set of independent variable

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published