Explain the normal form equation of the linear regression

Data Science, AI and ML
#1

The normal equation for linear regression is :

β=(XTX)-1XTY

This is also known as the closed-form solution for a linear regression model.

where,

Y=βTX is the equation that represents the model for the linear regression,

Y is the dependent variable or target column,

β is the vector of the estimates of the regression coefficient, which is arrived at using the normal equation,

X is the feature matrix that contains all the features in the form of columns. The thing to note down here is that the first column in the X matrix consists of all 1s, to incorporate the offset value for the regression line.