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@vikumn vikumn/eval.groovy
Last active Aug 29, 2015

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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/u.data"){ // relative (or absolute) path to the dataset. In the current format, it assumes that you have a folder named "ml-100k" containing the "u.data" 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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