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Last active August 29, 2015 14:02
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import org.grouplens.lenskit.knn.item.*
import org.grouplens.lenskit.transform.normalize.*
import org.grouplens.lenskit.eval.metrics.topn.*;
trainTest {
dataset crossfold("ml-100k") {
source csvfile("ml-100k/"){ // relative (or absolute) path to the dataset. In the current format, it assumes that you have a folder named "ml-100k" containing the "" file
delimiter "\t"
domain {
minimum 1.0
maximum 5.0
precision 1.0
algorithm("PersMean") {
bind ItemScorer to UserMeanItemScorer
bind (UserMeanBaseline, ItemScorer) to ItemMeanRatingItemScorer
metric RMSEPredictMetric
metric topNnDCG {
listSize 10
candidates ItemSelectors.allItems()
exclude ItemSelectors.trainingItems()
output "eval-results.csv"
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