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R-squared

A statistical measure that represents the proportion of the variance for a dependent variable that's explained by an independent variable or variables in a regression model.

AbbreviationR²
Categoryai

Overview

Also known as the 'Coefficient of Determination,' R-squared indicates how well the model fits the data. It ranges from 0 to 1 (though it can be negative for very poor models).

Interpretation

  • 1.0: The model explains 100% of the variance (perfect fit).
  • 0.0: The model explains none of the variance (no better than predicting the mean).

Limitations

  • Doesn't indicate bias: A high R-squared doesn't mean the model is good; it could be overfitted.
  • Increases with more features: Adding more variables will always increase R-squared, even if they are irrelevant. This is why Adjusted R-squared is often used instead.

Related Terms

Bias-Variance Tradeoff