plot_contribution_to_training_samples: Plot feature contributions to sample predictions from the...

In Mushriq/mixmap: Test package to share mixmap code

Plot feature contributions to sample predictions from the training set.

Description

This function plots the contribution (Shapley values) of the top features to a sample's predictions.

Usage

plot_contribution_to_training_samples(
  models,
  models_to_use,
  model_data,
  samples_to_use = NULL,
  lineage_to_use = NULL,
  n_features = 5,
  n_columns = 1,
  fixed_axis = TRUE,
  axis_limits = c(-0.05, 1),
  nudges_lr = c(0, 0),
  show_error = TRUE,
  highlight_significant = FALSE,
  replace_names = FALSE,
  sample_info = NULL,
  labels_data = NULL,
  sec_label = NULL,
  values_are_percentages = TRUE,
  decreasing = FALSE
)

Arguments

models	A list of models generated with make_xgb_models and has appended predictions with add_predictions.
models_to_use	A vector of model names to plot.
model_data	The training dataset used to generate the model.
n_features	The number of top contributors to show their individual contribution. All other predictors will have their contribution combined.
n_columns	Number of columns to plot in a grid when plotting more than one sample.
fixed_axis	If TRUE, the plot will be set to a fixed scale (-0.05 to 1). Default = FALSE.
show_error	If TRUE, a shaded area will be used to visualize prediction interval. Default = TRUE.
replace_names	If TRUE, the sample name will be replaced using get_cell_line_name. Must supply sample_info.
sample_info	If replace_names is TRUE, this must be supplied.
short_title	If using many columns, set to TRUE to shorten the title of the plot.

Examples

plot_contribution_to_training_sample(my_models, c("ko_ctnnb1","ko_myod1"), model_dataset, lineage_to_use = "soft_tissue")

Mushriq/mixmap documentation built on Jan. 28, 2024, 7:22 p.m.