Returns the explained variance regression score.
Returns the mean absolute error, which is a risk function corresponding to the expected value of the absolute error loss or l1-norm loss.
Returns the mean squared error, which is a risk function corresponding to the expected value of the squared error loss or quadratic loss.
objective function (scaled loss + regularization) at each iteration.
Returns R2, the coefficient of determination.
Residuals (label - predicted value)
Returns the root mean squared error, which is defined as the square root of the mean squared error.
Number of training iterations until termination