not able to use pearson similarity

[inkrement]

both, jaccard and cosine similarity work, but when I use pearson I get the following error:

> recc_model <- Recommender(data = R, method = "UBCF", parameter = list(method = "pearson"))
> recc_predicted <- predict(object = recc_model, newdata = R,n = 6)
Error in if (!is.null(attr(d, "method")) && tolower(attr(d, "method")) %in%  : 
  missing value where TRUE/FALSE needed

[mhahsler]

The following code seems to work for me (see below). Are you using the latest version (R and recommenderlab)? Please send me code and data that creates the problem.

 > data("MovieLense")
 > MovieLense100 <- MovieLense[rowCounts(MovieLense) >100,]
 > train <- MovieLense100[1:50] 
 > rec <- Recommender(train, method = "UBCF", list(method = "pearson"))
 > rec
    Recommender of type ‘UBCF’ for ‘realRatingMatrix’ 
    learned using 50 users.
 > predict(object = rec, newdata = MovieLense100, n = 6)
    Recommendations as ‘topNList’ with n = 6 for 358 users. 

[mhahsler]

Thanks for the bug report. Dissimilarity for binary data returns now the correct data type which fixes the issue.