Linear Regression

Linear Regression is a type of supervised ML algorithm that learns from the labelled dataset and maps the data points with the most optimized linear function, which can be used for prediction on a new dataset. It assumes a linear relationship between the input and output, i.e., the output changes at a constant rate as the input changes. A straight line represents this relationship.

[Diagram: Scatter plot with dependent variable (Y-axis) vs independent variable (X-axis), showing data points and line of regression. Labels: Independent Variable → Input, Dependent Variable → Output]

Type:
  Simple Linear Regression → Predicts the dependent variable using a single independent variable.
  Multiple Linear Regression → Uses two or more independent variables to predict the dependent variable.
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