Runs Score

Score based on Runs test statistic. Note that this test is not very strong. It utilizes only signs of the residuals. The score value is helpful in comparing models. It is worth pointing out that results of tests like p-value makes sense only when the test assumptions are satisfied. Otherwise test statistic may be considered as a score.

score_runs(object, variable = NULL, data = NULL, y = NULL, ...)

scoreRuns(object, variable = NULL)

Arguments

object	An object of class explainer created with function explain from the DALEX package.
variable	name of model variable to order residuals.
data	New data that will be used to calculate the score. Pass NULL if you want to use data from object.
y	New y parameter will be used to calculate score.
...	Other arguments dependent on the type of score.

Value

An object of class auditor_score.

Examples

dragons <- DALEX::dragons[1:100, ]

# fit a model
model_lm <- lm(life_length ~ ., data = dragons)

# create an explainer
lm_audit <- audit(model_lm, data = dragons, y = dragons$life_length)
#> Preparation of a new explainer is initiated
#>   -> model label       :  lm  (  default  )
#>   -> data              :  100  rows  8  cols 
#>   -> target variable   :  100  values 
#>   -> predict function  :  yhat.lm  will be used (  default  )
#>   -> predicted values  :  No value for predict function target column. (  default  )
#>   -> model_info        :  package stats , ver. 4.1.1 , task regression (  default  ) 
#>   -> predicted values  :  numerical, min =  585.8311 , mean =  1347.787 , max =  2942.307  
#>   -> residual function :  difference between y and yhat (  default  )
#>   -> residuals         :  numerical, min =  -88.41755 , mean =  -1.489291e-13 , max =  77.92805  
#>   A new explainer has been created!  

# caluclate score
score_runs(lm_audit)
#> Runs: -0.2867915