How is the R-Squared value used in assessing the performance of a regression model?
- Measures the error variance
- Measures the explained variance ratio
- Measures the model's complexity
- Measures the total sum of squares
The R-Squared value, also known as the coefficient of determination, measures the ratio of the explained variance to the total variance. It provides a statistical measure of how well the regression line approximates the real data points, with a value between 0 and 1. A higher R-Squared value indicates that more of the variance is captured by the model.
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