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rec.recommender.class=wrmf
rec.iterator.maximum=20
rec.user.regularization=0.01
rec.item.regularization=0.01
rec.factor.number=20
rec.recommender.isranking=true
rec.recommender.ranking.topn=10

#confidence weight coefficient, alpha in original paper
rec.wrmf.weight.coefficient=4.0