Evaluate the reach of recommender algorithms
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Key: MAHOUT-925
URL: https://issues.apache.org/jira/browse/MAHOUT-925
Project: Mahout
Issue Type: Improvement
Components: Collaborative Filtering
Affects Versions: 0.5
Reporter: Anatoliy Kats
Assignee: Sean Owen
Priority: Minor
The evaluation of a CF algorithm should include reach, the proportion of users
for whom a recommendation could be made. An algorithm usually has a cutoff
value on the confidence of the recommender, and if it is not high enough, no
recommendation is made. The number of requested recommendations, or this
parameter could be varied as part of the evaluation. The proposed patch adds
this.
My build with this patch breaks
testMapper(org.apache.mahout.classifier.df.mapreduce.partial.Step1MapperTest):
org.apache.mahout.classifier.df.node.Leaf.<init>(I)V . The test seems
unrelated to the patch, so I am assuming this is broken in the trunk head as
well. Unfortunately I am under a deadline, and I do not have time to write
tests for the patch.
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