oscar.cv.visu: Visualize cross-validation as a function of k

In oscar: Optimal Subset Cardinality Regression (OSCAR) Models Using the L0-Pseudonorm

Visualize cross-validation as a function of k

Description

This function plots the model performance as a function of cardinality for k-fold cross-validation. Performance metric depends on user choice and model family (i.e. lower MSE is good, higher C-index is good).

Usage

oscar.cv.visu(
  cv,
  add = FALSE,
  main = "OSCAR cross-validation",
  xlab = "Cardinality 'k'",
  ylab = "CV performance",
  ...
)

Arguments

cv	Matrix produced by oscar.cv; rows are cv-folds, cols are k-values
add	Should plot be added on top of an existing plot device
main	Main title
xlab	X-axis label
ylab	Y-axis label
...	Additional parameters passed on top the CV points

Value

This is a plotting function that does not return anything, but instead draws on an existing or a new graphics device.

Examples

if(interactive()){
  data(ex)
  fit <- oscar(x=ex_X, y=ex_Y, k=ex_K, w=ex_c, family='cox')
  fit_cv <- oscar.cv(fit, fold = 10, seed = 123)
  oscar.cv.visu(fit_cv)
}

oscar documentation built on Oct. 2, 2023, 5:08 p.m.