What Really is R2-Score in Linear Regression?

One of the most important metrics for evaluating a continuous target regression model

Benjamin Obi Tayo Ph.D.
3 min readNov 5, 2021
Figure shows how R2 Score determines goodness of fit. Image by author.

There are so many different metrics that can be used for evaluating regression models. In this article, we discuss several metrics that can be used for continuous target variable regression models. Among the many, R2 Score remains the most popular metric.

Metrics for Continuous Target Regression

If you are performing regression for a continuous outcome (i.e.linear regression, K-neighbors regression or support vector regression), then you may use metrics such as MSE, MAE, ME or R2 Score to evaluate the performance of your model.

Different metrics for evaluating a linear regression model. Image by author.

In the examples below, y represents the exact value, while y_hat represents the predicted value. We will assume our dataset has N observations.

  • MSE (Mean Square Error): Uses Euclidean distance to calculate the error. MSE gives the magnitude of the error only.
  • MAE (Mean Absolute Error): Uses Manhattan distance to calculate the error. MAE (like MSE) gives the magnitude of the error…

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Benjamin Obi Tayo Ph.D.
Benjamin Obi Tayo Ph.D.

Written by Benjamin Obi Tayo Ph.D.

Dr. Tayo is a data science educator, tutor, coach, mentor, and consultant. Contact me for more information about our services and pricing: benjaminobi@gmail.com

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