Plot List of Explanations

Plot List of Explanations

# S3 method for list
plot(x, ...)

Arguments

x

a list of explanations of the same class

...

other parameters

Value

An object of the class ggplot.

Examples

 # \donttest{
library("ranger")
titanic_ranger_model <- ranger(survived~., data = titanic_imputed, num.trees = 50,
                               probability = TRUE)
explainer_ranger  <- explain(titanic_ranger_model, data = titanic_imputed[,-8],
                             y = titanic_imputed$survived)
#> Preparation of a new explainer is initiated
#>   -> model label       :  ranger  (  default  )
#>   -> data              :  2207  rows  7  cols 
#>   -> target variable   :  2207  values 
#>   -> predict function  :  yhat.ranger  will be used (  default  )
#>   -> predicted values  :  No value for predict function target column. (  default  )
#>   -> model_info        :  package ranger , ver. 0.14.1 , task classification (  default  ) 
#>   -> predicted values  :  numerical, min =  0.0005555556 , mean =  0.3205157 , max =  0.9883577  
#>   -> residual function :  difference between y and yhat (  default  )
#>   -> residuals         :  numerical, min =  -0.831336 , mean =  0.001641051 , max =  0.8773243  
#>   A new explainer has been created!  
mp_ranger <- model_performance(explainer_ranger)

titanic_ranger_model2 <- ranger(survived~gender + fare, data = titanic_imputed,
                                num.trees = 50, probability = TRUE)
explainer_ranger2  <- explain(titanic_ranger_model2, data = titanic_imputed[,-8],
                              y = titanic_imputed$survived,
                              label = "ranger2")
#> Preparation of a new explainer is initiated
#>   -> model label       :  ranger2 
#>   -> data              :  2207  rows  7  cols 
#>   -> target variable   :  2207  values 
#>   -> predict function  :  yhat.ranger  will be used (  default  )
#>   -> predicted values  :  No value for predict function target column. (  default  )
#>   -> model_info        :  package ranger , ver. 0.14.1 , task classification (  default  ) 
#>   -> predicted values  :  numerical, min =  0.1572722 , mean =  0.3224717 , max =  0.9032262  
#>   -> residual function :  difference between y and yhat (  default  )
#>   -> residuals         :  numerical, min =  -0.8677249 , mean =  -0.0003149388 , max =  0.8427278  
#>   A new explainer has been created!  
mp_ranger2 <- model_performance(explainer_ranger2)

plot(list(mp_ranger, mp_ranger2), geom = "prc")

plot(list(mp_ranger, mp_ranger2), geom = "roc")

tmp <- list(mp_ranger, mp_ranger2)
names(tmp) <- c("ranger", "ranger2")
plot(tmp)

# }