Area Over the Curve for REC Curves

Source: R/score_rec.R

The area over the Regression Error Characteristic curve is a measure of the expected error for the regression model.

score_rec(object, data = NULL, y = NULL, ...)

scoreREC(object)

Arguments

object

An object of class explainer created with function explain from the DALEX package.
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.

References

J. Bi, and K. P. Bennet, "Regression error characteristic curves," in Proc. 20th Int. Conf. Machine Learning, Washington DC, 2003, pp. 43-50

See also

plot_rec

Examples

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

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

# create an explainer
lm_audit <- audit(lm_model, 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!  

# calculate score
score_rec(lm_audit)

#> rec: 31.06331