recommenderlab (version 0.1-0)

evaluate: Evaluate a Recommender Models

Description

Evaluates a single or a list of recommender model given an evaluation scheme.

Usage

evaluate(x, method, ...)
## S3 method for class 'evaluationScheme,character':
evaluate(x, method, n=1:10, 
parameter=NULL, progress = TRUE, keepModel=FALSE)
## S3 method for class 'evaluationScheme,list':
evaluate(x, method, n=1:10, 
parameter=NULL, progress = TRUE, keepModel=FALSE)

Arguments

x

an evaluation scheme (class "evaluationScheme").

method

a character string or a list. If a single character string is given it defines the recommender method used for evaluation. If several recommender methods need to be compared, method contains a nested list. Each element describes a reco

n

N (number of recommendations) of the top-N lists generated.

parameter

parameters for the recommender algorithm.

progress

report progress?

keepModel

store used recommender models?

...

further arguments.

Value

• Returns an object of class "evaluationResults" or if method is a list an object of class "evaluationResultList".

See Also

evaluationScheme, evaluationResults. evaluationResultList.

Examples

data("MSWeb")
MSWeb10 <- sample(MSWeb[rowCounts(MSWeb) >10,], 100)

## create an evaluation scheme
es <- evaluationScheme(MSWeb10, method="cross-validation",
        k=4, given=3)

## run evaluation
ev <- evaluate(es, "POPULAR")
ev

## look at the results
avg(ev)
plot(ev, type="o", annotate = TRUE)

## now run evaluate with a list
algorithms <- list(
		RANDOM = list(name = "RANDOM", param = NULL),
		POPULAR = list(name = "POPULAR", param = NULL),
		UBCF = list(name = "UBCF", param = NULL),
		IBCF = list(name = "IBCF", param=NULL),
		AR = list(name = "AR", param=NULL)
		)

evlist <- evaluate(es, algorithms)
plot(evlist, legend="topright")

## select the first results
evlist[[1]]