surv_ceteris_paribus: Helper functions for 'predict_profile.R'

In survex: Explainable Machine Learning in Survival Analysis

Helper functions for predict_profile.R

Description

Helper functions for predict_profile.R

Helper functions for predict_profile.R

Usage

surv_ceteris_paribus(x, ...)

## S3 method for class 'surv_explainer'
surv_ceteris_paribus(
  x,
  new_observation,
  variables = NULL,
  categorical_variables = NULL,
  variable_splits = NULL,
  grid_points = 101,
  variable_splits_type = "uniform",
  center = FALSE,
  output_type = "survival",
  ...
)

Arguments

x	an explainer object - model preprocessed by the explain() function
...	other parameters, currently ignored
new_observation	a new observation for which predictions need to be explained
variables	character, names of the variables to be included in the calculations
categorical_variables	character vector, names of variables that should be treated as categories (factors are included by default)
variable_splits	named list of splits for variables, in most cases created with internal functions. If NULL then it will be calculated based on validation data available in the explainer
grid_points	maximum number of points for profile calculations. Note that the final number of points may be lower than grid_points. Will be passed to internal function. By default 101.
variable_splits_type	character, decides how variable grids should be calculated. Use "quantiles" for percentiles or "uniform" (default) to get uniform grid of points.

Value

A data.frame containing the result of the calculation.

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