Class CrossValidation — CrossValidation • quadrupen

Class of object returned by the QuadrupenFit$cross_validate() method or the cross_validate() function. Owns print() and plot() methods.

Active bindings

data: a data frame containing the mean cross-validated error and its associated standard error for each values of lambda1 and lambda2.
folds: list of K vectors indicating the folds used for cross-validation.
lambda1: vector of $\lambda_1$ ($\ell_1$ or $\ell_\infty$ penalty levels) for which each cross-validation has been performed.
lambda2: vector (or scalar) of $\ell_2$-penalty levels for which each cross-validation has been performed.
lambda1_min: level of $\lambda_1$ that minimizes the error estimated by cross-validation.
lambda2_min: level of $\lambda_2$ that minimizes the error estimated by cross-validation.
lambda1_1se: largest level of $\lambda_1$ such as the cross-validated error is within 1 standard error of the minimum.
lambda2_1se: largest level of $\lambda_2$ such that the cross-validated error is within 1 standard error of the minimum (only relevant for ridge regression).

Constructor for a CrossValidation object Should be called internally by an object QuadrupenFit$cross_validate()

CrossValidation$new(cv_error, folds)

User friendly print method

CrossValidation$show()

User friendly print method

CrossValidation$print()

Plot 1-dimensional cross-validation

CrossValidation$plotCV_1D(
  log_scale = TRUE,
  title = "Cross-validation error",
  se = TRUE
)

a ggplot object

Plot 2-dimensional cross-validation output (grid lambda1 x lambda2)

CrossValidation$plotCV_2D(title = "Cross-validation error")

a ggplot2 object

Plot cross-validation job by choosing the most appropriate output (1D- or 2D)

CrossValidation$plot(log_scale = TRUE, title = "Cross-validation error")

a ggplot object

The objects of this class are cloneable with this method.

CrossValidation$clone(deep = FALSE)