Linear Regression -- Occam's Razor of Predictive Machine Learning Modeling

Linear regression is when linear predictors (or independent variables) are used to predict a dependent variable. In this case, y is the dependent variable and x is the independent variable (c is a constant). The goal of a linear regression model is to determine the best coefficient (a in the example above) for x to most accurately predict y. Now let's generalize that example, which is also known as mulitple linear regression. In a multiple linear regression model, the goal is to find the line of best fit that describes the relationship between the dependent variable and multiple independent variables.