Introduction to
Linear Regression
Linear regression is a type of supervised machine learning algorithm that
computes the linear relationship between the dependent variable and one or
more independent features by fitting a linear equation to observed data.
When there is only one independent feature, it is known as Simple Linear
Regression, and when there are more than one feature, it is known as
Multiple Linear Regression.
Eg. Salary and Work
, Types Of Linear Regression:
Simple Linear Regression:
If a single independent variable is used to predict the value of a numerical
dependent variable, then such a Linear Regression algorithm is called Simple
Linear Regression.
Multiple Linear regression:
If more than one independent variable is used to predict the value of a numerical
dependent variable, then such a Linear Regression algorithm is called Multiple
Linear Regression.
Linear Regression
Linear regression is a type of supervised machine learning algorithm that
computes the linear relationship between the dependent variable and one or
more independent features by fitting a linear equation to observed data.
When there is only one independent feature, it is known as Simple Linear
Regression, and when there are more than one feature, it is known as
Multiple Linear Regression.
Eg. Salary and Work
, Types Of Linear Regression:
Simple Linear Regression:
If a single independent variable is used to predict the value of a numerical
dependent variable, then such a Linear Regression algorithm is called Simple
Linear Regression.
Multiple Linear regression:
If more than one independent variable is used to predict the value of a numerical
dependent variable, then such a Linear Regression algorithm is called Multiple
Linear Regression.
