Data Science, Regularization, Machine Learning, Editors Pick, Hands On Tutorials.
Ordinary Least Squares. The premise of Ordinary Least Squares (OLS) is that you’ll pick the coefficients that minimize the residual sum of squares, i.e., the total squared difference between your predictions and the observed data[1]. With the residual sum of squares not all residuals are treated