Using Myrrix in R

Myrrix

install.packages('Myrrix')
install.packages("devtools")
install.packages("rJava")
install.packages("ffbase")
library(devtools)
install_github("Myrrix-R-interface", "jwijffels", subdir="/Myrrixjars/pkg")
install_github("Myrrix-R-interface", "jwijffels", subdir="/Myrrix/pkg")

library(Myrrix)
## Download example dataset
inputfile <- file.path(tempdir(), "audioscrobbler-data.subset.csv.gz")
download.file(url="http://dom2bevkhhre1.cloudfront.net/audioscrobbler-data.subset.csv.gz", destfile = inputfile)

## Set hyperparameters
setMyrrixHyperParameters(params=list(model.iterations.max = 2, model.features=10, model.als.lambda=0.1))
x <- getMyrrixHyperParameters(parameters=c("model.iterations.max","model.features","model.als.lambda"))
str(x)

## Build a model which will be stored in getwd() and ingest the data file into it
recommendationengine <- new("ServerRecommender", localInputDir="/tmp/RtmpeuoEjq/")
ingest(recommendationengine, inputfile)
await(recommendationengine)

## Get all users/items and score alongside the recommendation model
items <- getAllItemIDs(recommendationengine)
users <- getAllUserIDs(recommendationengine)
estimatePreference(recommendationengine, userID=users[1], itemIDs=items[1:20])
estimatePreference(recommendationengine, userID=users[10], itemIDs=items)
mostPopularItems(recommendationengine, howMany=10L)
recommend(recommendationengine, userID=users[5], howMany=10L)