vis_model_fit: Visualise Generative Model Fit

In ICBioMark: Data-Driven Design of Targeted Gene Panels for Estimating Immunotherapy Biomarkers

Description

A function to visualise how well a general model has fitted to a mutation dataset across cross-validation folds. Designed to produce a similar output to glmnet's function plot.cv.glmnet.

Usage

vis_model_fit(
  gen_model,
  x_sparsity = FALSE,
  y_sparsity = FALSE,
  mut_type = NULL
)

Arguments

gen_model	(list) A generative model fitted by fit_gen_model()
x_sparsity	Show model sparsity on x axis rather than lambda.
y_sparsity	Show model sparsity on y axis rather than deviance.
mut_type	Produce separate plots for each mutation type.

Value

Summary plot of the generative model fit across folds.

Examples

p <- vis_model_fit(example_gen_model)

ICBioMark documentation built on Nov. 15, 2021, 5:09 p.m.