surv_feature_importance: Helper functions for 'model_parts.R'

In survex: Explainable Machine Learning in Survival Analysis

Helper functions for model_parts.R

Description

This function is used to calculate permutational feature importance using a time-dependent metric. The result is the change in loss function at each time point after permuting each selected variable.

Usage

surv_feature_importance(x, ...)

## S3 method for class 'surv_explainer'
surv_feature_importance(
  x,
  loss_function = NULL,
  ...,
  type = c("raw", "ratio", "difference"),
  B = 10,
  variables = NULL,
  variable_groups = NULL,
  N = NULL,
  label = NULL
)

Arguments

x	an explainer object - model preprocessed by the explain() function
...	other parameters, currently ignored
loss_function	a function that will be used to assess variable importance, by default loss_brier_score for survival models. The function can be supplied manually but has to have these named parameters (y_true, risk, surv, times), where y_true represents the survival::Surv object with observed times and statuses, risk is the risk score calculated by the model, and surv is the survival function for each observation evaluated at times.
type	a character vector, if "raw" the results are losses after the permutation, if "ratio" the results are in the form loss/loss_full_model and if "difference" the results are of the form loss - loss_full_model'
B	numeric, number of permutations to be calculated
variables	a character vector, names of variables to be included in the calculation
variable_groups	a list of character vectors of names of explanatory variables. For each vector, a single variable importance measure is computed for the joint effect of the variables which names are provided in the vector. By default, variable_groups = NULL, in which case variable importance measures are computed separately for all variables indicated in the variables argument.
N	numeric, number of observations that are to be sampled from the dataset for the purpose of calculation
label	label of the model, if provided overrides explainer$label

Details

Note: This function can be run within progressr::with_progress() to display a progress bar, as the execution can take long, especially on large datasets.

Value

A data.frame containing results of the calculation.

survex documentation built on Oct. 25, 2023, 1:06 a.m.