pathofmpred_control: Define model-development settings

In PathoFMPred: Tumour Feature Models from Pathology Representations

Define model-development settings

Description

Define model-development settings

Usage

pathofmpred_control(
  components = 1:20,
  outer_folds = 5L,
  inner_folds = 5L,
  repeats = 1L,
  scaling = "centering",
  method = "plssvd",
  backend = NULL,
  binary_selection = "AUROC",
  continuous_selection = "auto",
  seed = 1L,
  minimum_continuous = 50L,
  minimum_binary_class = 20L,
  rsvd_oversample = NULL,
  rsvd_power = NULL
)

Arguments

components	Candidate PLS component counts.
outer_folds, inner_folds	Numbers of nested cross-validation folds.
repeats	Number of independently seeded nested evaluations.
scaling, method, backend	Arguments passed to fastPLS.
binary_selection	Inner-CV objective for binary outcomes. AUROC is the default because the resulting score ranking is independent of prevalence- specific class priors.
continuous_selection	Inner-CV objective for continuous outcomes.
seed	Initial random seed.
minimum_continuous	Minimum labelled patients for a continuous model.
minimum_binary_class	Minimum patients in each binary class.
rsvd_oversample, rsvd_power	Optional overrides. 'NULL' preserves the installed fastPLS defaults.

Value

A settings list for [create_pathofmpred_object()].

Examples

settings <- pathofmpred_control(
  components = 1:3, outer_folds = 3, inner_folds = 3, seed = 42
)
settings$components

PathoFMPred documentation built on Nov. 12, 2026, 5:10 p.m.