recommenderlab z parametrami dla realRatingMatrix

IBCF.R

recommenderRegistry$set_entry(
  method="IBCF", dataType = "realRatingMatrix", fun=REAL_IBCF,
  description="Recommender based on item-based collaborative filtering (real data).",
  parameters=.REAL_IBCF_params)


.REAL_IBCF_params <- list(
  k = 30, 
  method="Cosine",
  normalize = "center", 
  normalize_sim_matrix = FALSE,
  alpha = 0.5,
  na_as_zero = FALSE,
  minRating = NA
)

metody.R

dissimilarity method for binaryRatingMatrix:
	"jaccard"
	"karypis"
	"conditional"

dissimilarity method for realRatingMatrix:
	"cosine"
	"karypis"
	"conditional"
	"pearson"

similarity:
	"cosine"
	"karypis"
	"conditional"


normalize:
	"center"
	"Z-score"

PCA.R

recommenderRegistry$set_entry(
  method="PCA", dataType = "realRatingMatrix", fun=REAL_PCA,
  description="Recommender based on PCA approximation (real data).",
  parameters = .REAL_PCA_param)


.REAL_PCA_param <- list(
  categories = 20,
  method="Cosine",
  normalize = "center",
  normalize_sim_matrix = FALSE,
  alpha = 0.5,
  na_as_zero = FALSE,
  minRating = NA
)

POPULAR.R

nie ma parametrów

RANDOM.R

nie ma parametrów

Recommenderlab.R

Tutaj widać, że z recommenderRegistry brana jest odpowiednia metoda a potem dla tej metody wołana 
jest funkcja do której przekazywane są parametry prosto z wywołania Recommender(parameter=...)

setMethod("Recommender", signature(data = "ratingMatrix"),
function(data, method, parameter = NULL) {
	recom <- recommenderRegistry$get_entry(
		method = method, dataType = class(data))
	if(is.null(recom)) stop(paste("Recommender method", method, 
			"not implemented for data type", class(data),"."))

	## this is expected to return a valid Recommender object
	recom$fun(data = data, parameter = parameter)
})

SVD.R

.REAL_SVD_param <- list(
  categories = 50,
  method="Cosine",
  normalize = "center",
  normalize_sim_matrix = FALSE,
  alpha = 0.5,
  treat_na = "median",
  minRating = NA
)

recommenderRegistry$set_entry(
  method="SVD", dataType = "realRatingMatrix", fun=REAL_SVD,
  description="Recommender based on SVD approximation (real data).",
  parameters = .REAL_SVD_param)

UBCF.R

.REAL_UBCF_param <- list( 
  method = "cosine", 
  nn = 25, 
  sample = FALSE,
  ## FIXME: implement weighted = TRUE,
  normalize="center",
  minRating = NA
)


recommenderRegistry$set_entry(
  method="UBCF", dataType = "realRatingMatrix", fun=REAL_UBCF,
  description="Recommender based on user-based collaborative filtering (real data).",
  parameters=.REAL_UBCF_param)