Why do we use "Sum of Squared Errors" as loss function in linear regression?
115126
What is a loss function in decision theory?
61083
Why is Newton's method not widely used in machine learning?
27054
Sum of squares of residuals instead of sum of residuals
9444
In linear regression, when is it appropriate to use the log of an independent variable instead of the actual values?
2180
What do the subscripts in expectations mean in loss function
22668
Linear vs. nonlinear regression
23868
Normality assumption in linear regression
135975
Why would one suppress the intercept in linear regression?
102459
Why use gradient descent for linear regression, when a closed-form math solution is available?
25409
Why does k-fold cross validation generate an MSE estimator that has higher bias, but lower variance then leave-one-out cross-validation?
42773
How to minimize residual sum of squares of an exponential fit?
74257
Why is coefficient of determination used to assess fit of a least squares line?
20216
Why do residuals in linear regression always sum to zero when an intercept is included?
17815
Understanding the minimization of mean squared error function
45364
Why is there a $2$ at the denominator of the mean squared error function?
20900
Regression without intercept: deriving $\hat{\beta}_1$ in least squares (no matrices)
88139
Why binary crossentropy can be used as the loss function in autoencoders?