Multiple linear regression is a technique used to train a linear model, that assumes that there are linear relationships between multiple predictor variables () and a continuous target variable (
). The general equation for a multiple linear regression with m predictor variables is as follows:
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Training a linear regression model involves estimating the values of the coefficients for each of the predictor variables denoted by the letter . In the preceding equation,
denotes an error term, which is normally distributed, and has zero mean and constant variance. This is represented as follows:
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Various techniques can be used to build a linear regression model. The most frequently used is the ordinary least square (OLS) estimate. The OLS method is used to produce a linear regression line...