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What is Linear Regression?

Answer»

Linear Regression is the oldest, simple and widely used supervised machine learning algorithm for PREDICTIVE analysis. It’s a method to predict a target variable by fitting the best linear relationship between the dependent and independent variable.

The best fitting line can be found by making sure that the sum of all the distances between the shape and the actual observations at each point is as small as possible. The fit of the shape is “best” in the SENSE that no other position WOULD produce less ERROR given the choice of shape.

Types of Linear Regression:

  1. Simple Linear Regression - This method uses a single independent variable to predict a dependent variable by fitting a best linear relationship.
  2. Multiple Linear Regression - This method uses more than one independent variable to predict a dependent variable by fitting a best linear relationship.


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