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rec.recommender.class=lda
rec.iterator.maximum=1000
rec.topic.number = 10
rec.recommender.isranking=true
rec.recommender.ranking.topn=10
rec.user.dirichlet.prior=0.01
rec.topic.dirichlet.prior=0.01
rec.pgm.burnin=100
rec.pgm.samplelag=10
data.splitter.cv.number=5
# (0.0 maybe a better choose than -1.0)
data.convert.binarize.threshold=0.0