Residual Sum Of Squares (Rss)

Measures the overall difference between actual data and the values predicted by an estimation model. The differences are squared and then added. It represents unexplained variation – a smaller RSS means that the model fits the data well. Also called the Sum of Squared Errors of prediction (SSE).

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