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From Zia mel <ziad.kame...@gmail.com>
Subject Finding best NearestNUserNeighborhood size
Date Wed, 23 Jan 2013 13:01:21 GMT
Hi
I used NearestNUserNeighborhood with RMSE in a user recommender that
use PearsonCorrelationSimilarity , I found that changing the
neighborhood size has no clear pattern or effect. Sometimes it
increase others decrease. While using the neighborhood size with
precision has a better pattern. Any reason? Another point is that the
RMSE change for every run since it choose different sample , so would
running the code for 10 or 20 times and taking the average be a good
idea or there is better thing to do?

//-- RUN 1
 2,  0.5523623146152608
 3,  0.5425283201773704
 4,  0.669846658662311
 5,  0.5956616542334392
 6,  0.6033911039809353
 7,  0.6135206544496685
 8,  0.5740444208649034
 9,  0.642798288443049
 10,  0.6266535555651472

//-- RUN 2
 2,  0.5415411343523825
 3,  0.6784589323396696
 4,  0.6347069968141124
 5,  0.6968820296725008
 6,  0.5953849874479478
 7,  0.6791828191904128
 8,  0.6072462830257853
 9,  0.6461346217476011
 10,  0.6043919119341171

Thanks !

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