TLDR
Linear Regression is a predictive statistical approach for modelling relationship between a dependent variable with a given set of independent variables. The linear equation assigns one scale factor to each input value or column, called a coefficient and represented by the capital Greek letter Beta (B) For more than one independent variable, the process is called as multiple linear regression. The General equation for a Multiple linear regression with p - independent variables looks like this: B0 + B1*x, where B0 represents the intercept or the bias coefficient.via the TL;DR App
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Written by afroz-chakure | Enjoys Reading, writes amazing blogs, and can talk about Machine Learning for hours.
