query: What makes mean square error so good?
positive_passages.docid: 146616
positive_passages.text: Why is the squared difference so commonly used?
negative_passages.docid: 54112
negative_passages.text: Linear regression what does the F statistic, R squared and residual standard error tell us?
negative_passages.docid: 157923
negative_passages.text: RMSProp Squared Gradients
negative_passages.docid: 52136
negative_passages.text: Linear regression with Laplace errors
negative_passages.docid: 12817
negative_passages.text: Determining true mean from noisy observations
negative_passages.docid: 111654
negative_passages.text: Moving-average model error terms
negative_passages.docid: 10730
negative_passages.text: Proof that regression residual error is an unbiased estimate of error variance
negative_passages.docid: 16209
negative_passages.text: Importance of optimizing the correct loss function
negative_passages.docid: 1290
negative_passages.text: Expectation of squared error
negative_passages.docid: 57850
negative_passages.text: Bounding an Error on the inverse.
negative_passages.docid: 2898
negative_passages.text: What's the MSE of $\hat{Y}$ in ordinary least squares using bias-variance decomposition?
negative_passages.docid: 99651
negative_passages.text: Why does ridge estimate become better than OLS by adding a constant to the diagonal?
negative_passages.docid: 45342
negative_passages.text: Generalization of Mean Value Theorem to functions, $f: \mathbb{R}^n \rightarrow \mathbb{R}^n$
negative_passages.docid: 26250
negative_passages.text: Robust mean estimation with O(1) update efficiency
negative_passages.docid: 141861
negative_passages.text: What is meant by the variance of *functions* in *Introduction to Statistical Learning*?
negative_passages.docid: 42773
negative_passages.text: How to minimize residual sum of squares of an exponential fit?
negative_passages.docid: 64409
negative_passages.text: Mean absolute error OR root mean squared error?