Plot Model Performance Metrics for Survival Models

This function plots objects of class "surv_model_performance" - visualization of metrics of different models created using the model_performance(..., type="metrics") function.

# S3 method for surv_model_performance
plot(
  x,
  ...,
  metrics = NULL,
  metrics_type = "time_dependent",
  title = "Model performance",
  subtitle = "default",
  facet_ncol = NULL,
  colors = NULL,
  rug = "all",
  rug_colors = c("#dd0000", "#222222")
)

Arguments

x: an object of class "surv_model_performance" to be plotted
...: additional objects of class "surv_model_performance" to be plotted together
metrics: character, names of metrics to be plotted (subset of C/D AUC", "Brier score" for metrics_type %in% c("time_dependent", "functional") or subset of "C-index","Integrated Brier score", "Integrated C/D AUC" for metrics_type == "scalar"), by default (NULL) all metrics of a given type are plotted
metrics_type: character, either one of c("time_dependent","functional") for functional metrics or "scalar" for scalar metrics
title: character, title of the plot
subtitle: character, subtitle of the plot, 'default' automatically generates "created for XXX, YYY models", where XXX and YYY are the explainer labels
facet_ncol: number of columns for arranging subplots
colors: character vector containing the colors to be used for plotting variables (containing either hex codes "#FF69B4", or names "blue")
rug: character, one of "all", "events", "censors", "none" or NULL. Which times to mark on the x axis in geom_rug().
rug_colors: character vector containing two colors (containing either hex codes "#FF69B4", or names "blue"). The first color (red by default) will be used to mark event times, whereas the second (grey by default) will be used to mark censor times.

Value

An object of the class ggplot.

Examples

library(survival)
library(survex)

# \donttest{
model <- randomForestSRC::rfsrc(Surv(time, status) ~ ., data = veteran)
exp <- explain(model)
#> Preparation of a new explainer is initiated 
#>   -> model label       :  rfsrc (  default  ) 
#>   -> data              :  137  rows  6  cols (  extracted from the model  ) 
#>   -> target variable   :  137  values ( 128 events and 9 censored , censoring rate = 0.066 ) (  extracted from the model  ) 
#>   -> times             :  50 unique time points , min = 1.5 , median survival time = 80 , max = 999 
#>   -> times             :  (  generated from y as uniformly distributed survival quantiles based on Kaplan-Meier estimator  ) 
#>   -> predict function  :  sum over the predict_cumulative_hazard_function will be used (  default  ) 
#>   -> predict survival function  :  stepfun based on predict.rfsrc()$survival will be used (  default  ) 
#>   -> predict cumulative hazard function  :  stepfun based on predict.rfsrc()$chf will be used (  default  ) 
#>   -> model_info        :  package randomForestSRC , ver. 3.2.3 , task survival (  default  ) 
#>   A new explainer has been created!  

m_perf <- model_performance(exp)
plot(m_perf)
#> Warning: Removed 1 row containing missing values or values outside the scale range
#> (`geom_line()`).

# }

Arguments

Value

See also

Examples