require(recommenderlab)
data(MovieLense)
x <- getData.frame(MovieLense)
x$itemid <- as.integer(as.factor(x$item))
x$userid <- as.integer(as.factor(x$user))
x$rating <- as.numeric(x$rating)
x <- head(x, 2000)
movielensestream <- datastream_dataframe(data=x)
movielensestream$get_points(3)
ctrl <- MOAoptions(model = "BRISMFPredictor", features = 10)
brism <- BRISMFPredictor(control=ctrl)
mymodel <- trainMOA(model = brism, rating ~ userid + itemid,
data = movielensestream, chunksize = 1000, trace=TRUE)
overview <- summary(mymodel$model)
str(overview)
predict(mymodel, head(x, 10), type = "response")
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