Linear Regression

Linear regression is one of the simplest and most widely used algorithms for predictive modeling. It works by finding the relationship between a dependent variable and one or more independent variables.

Formula

The formula for simple linear regression is:

[ y = mx + b ]

Where:

• ( y ) is the predicted value
• ( m ) is the slope of the line (coefficient)
• ( x ) is the input feature
• ( b ) is the y-intercept

Example Use Cases

• Predicting house prices based on features like square footage and location
• Estimating a person’s weight based on their height

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