getAUC: Returns the Area under the ROC curve.

In ludovikcoba/rrecsys: Environment for Evaluating Recommender Systems

Returns the Area under the ROC curve.

Description

Computes the Area Under the ROC curve for a recommendation task of an algorithm with its given configuration and based on the given evaluation model.

Usage

getAUC(model, ...)
## S4 method for signature 'evalModel'
getAUC(model, alg, ... )

Arguments

model	Object of type evalModel. See evalModel-class.
alg	The algorithm to be used in the evaluation. Of class character.
...	other attributes specific to the algorithm to be deployed. Refer to rrecsys.

Value

Returns a data frame with the AUC for each of the k-folds defined in the evaluation model and the overall average.

References

T. Fawcett, “ROC Graphs: Notes and Practical Considerations for Data Mining Researchers ROC Graphs : Notes and Practical Considerations for Data Mining Researchers,”, HP Inven., p. 27, 2003.

See Also

evalModel-class, rrecsys.

Examples

  x <- matrix(sample(c(NA, 1:5), size = 200, replace = TRUE, 
        prob = c(.6,.8,.8,.8,.8,.8)), nrow = 20, byrow = TRUE)
  
  x <- defineData(x)
        
  e <- evalModel(x, 5)
  
  auc <- getAUC(e, "FunkSVD", k = 4) 
  
  auc         
  
  

ludovikcoba/rrecsys documentation built on May 17, 2022, 2:33 a.m.