Hi, I have been digging into Mahout on Hadoop for the pas few days. I was wondering the recommendation algorithm that is used in RecommenderJob.java. For example:
bin/hadoop jar /opt/mahout/core/target/mahout-core-0.7-SNAPSHOT-job.jar org.apache.mahout.cf.taste.hadoop.item.RecommenderJob -Dmapred.input.dir=input/input.txt -Dmapred.output.dir=output --usersFile input/users.txt --booleanData By executing this command, is either item-based or user-based recommendation algorithm being used? And does specifying "--similarityClassname" in the command have anything to do with choosing item-based or user-based algorithm for the recommendation? The help is appreciated in advance, Rich
