mahout-user mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
From pranay venkata <>
Subject Re: Recommendations on binary ratings
Date Sat, 26 Jun 2010 18:22:44 GMT
Thanks to all for immediate responses.

I have tested my binary recommender on one million dataset by dividing it
into 80 % train , 20 % test data-set and i observe  an average precision
value as 0.22 (i.e out of 20 recommendations produced by the recommender
,there are around 5 matches with items in the test data-set)  and average
recall value to be 0.0135 for my recommendations.
I would like to know the quality of  these recommendations on the given
precision and recall values  ? how to estimate the quality of a recommender
on the values of  precision and recall and how much better could it be
improved practically  ?


On Fri, Jun 11, 2010 at 6:00 PM, pranay venkata <> wrote:

>  Hi,
> I'm a newbie to mahout.My aim is to produce recommendations on binary user
> purchased data.So i applied item-item similarity model in computing top N
> recommendations for movie lens data assuming 1-3 ratings as a 0 and 4-5
> ratings as a 1.Then i tried evaluating my recommendations with the ratings
> in the test-data but hardly there have been two or three matches from my top
> 20 recommendations to the top rated items in test data and no match for most
> users.
> So are my recommendations totally bad by nature or do i need to go for a
> different measure for evaluating my recommendations ?
> Please help me ! Thanks in advance.
> Pranay, 2nd yr ,UG student.


  • Unnamed multipart/alternative (inline, None, 0 bytes)
View raw message