A head start to Linear Regression

Types of Linear Regression

  1. Simple Linear Regression

1. Simple Linear Regression

A simple ML model using Linear Regression
slope
intercept
Linear Regression from Scratch

2. Multiple Linear Regression

Hyperplane equation
  • y = the predicted value of the dependent variable
  • B0 = the y-intercept (value of y when all other parameters are set to 0)
  • B1X1= the regression coefficient (B1) of the first independent variable (X1) (a.k.a. the effect that increasing the value of the independent variable has on the predicted y value)
  • … = do the same for however many independent variables you are testing
  • BnXn = the regression coefficient of the last independent variable
  • e = model error (a.k.a. how much variation there is in our estimate of y)

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Saurav Thakur

Saurav Thakur

Machine Learning Enthusiast

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