Implementation of Linear Regression

Quick overview of linear regression

Linear regression, as you may know, plots a straight line or plane called the hyperplane that predicts the target value of data inputs by determining the dependence between the dependent variable (y) and its changing independent variables (X). In a p-dimensional space, a hyperplane is a subspace equivalent to dimension p−1.

Thus, in a two-dimensional space, a hyperplane is a one-dimensional subspace/flat line. In three-dimensional space, a hyperplane is effectively a two-dimensional subspace. Although it becomes difficult to visualize a hyperplane in four or more dimensions, the notion of a p−1 hyperplane still applies.