Evaluation Metrics for Regression Analysis

These terms will come up, and it's good to get familiar with them if you aren't already: Goodness of fit is typically a term used to describe how well a dataset aligns with a certain statistical distribution. Here, we're going to think of it as a way of describing how well our model is fitted to our data. If we can think about our regression model in terms of the imaginary "best-fit" line it produces, then it makes sense that we would want to know how well this line matches our data. This goodness of fit can be quantified in a variety of ways, but the R² and the adjusted R² score are two of the most common methods for describing how well our model is capturing the variance in our target data. R² -- also called the coefficient of determination -- is a statistical measure representing the amount of variance for a dependent variable that is captured by your model's predictions.