Comments (3)
Hi. I finally found some time to look at this. I just checked and could not reproduce the problem. Can you post some code that reproduces the behavior? Thanks!
from recommenderlab.
I have an example:
ratings <- read.csv('csv/rating_final.csv')
binaryMatrix <- as(ratings,"binaryRatingMatrix")
scheme <- evaluationScheme(binaryMatrix, method = "cross-validation", k=5, train = 0.7, given = -1)
methods <- list(
popular = list(name = "POPULAR", param = NULL),
`user-based CF` = list(name = "UBCF", param = list(method = "cosine", nn = 3)),
`item-based CF` = list(name = "IBCF", param = list(method = "cosine", k = 3)),
AR = list(name="AR", param = list(supp=0.05,conf=0.5))
)
results <- evaluate(scheme, methods, type="topNList", n = c(1,2,5), progress = FALSE)
Although the progress parameter is false, the output is:
POPULAR run fold/sample [model time/prediction time]
1 [0sec/0.116sec]
2 [0sec/0.112sec]
3 [0sec/0.144sec]
4 [0.004sec/0.16sec]
5 [0.004sec/0.172sec]
UBCF run fold/sample [model time/prediction time]
1 [0.004sec/0.232sec]
2 [0sec/0.228sec]
3 [0sec/0.228sec]
4 [0.004sec/0.22sec]
5 [0.004sec/0.224sec]
IBCF run fold/sample [model time/prediction time]
1 [0.04sec/0.02sec]
2 [0.04sec/0.028sec]
3 [0.04sec/0.032sec]
4 [0.04sec/0.02sec]
5 [0.036sec/0.016sec]
AR run fold/sample [model time/prediction time]
1 [0.028sec/0.812sec]
2 [0.032sec/0.788sec]
3 [0.036sec/1.072sec]
4 [0.044sec/0.996sec]
5 [0.04sec/1.012sec]
The csv/rating_final.csv file is the one inside this zip file on UCI repository.
I think this just occurs when using methods list and probably due this code.
Shouldn't the progress parameter be passed down?
Sorry if it wasn't the best way to comment.
from recommenderlab.
If I'm not wrong, please consider the PR 18 .
from recommenderlab.
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