okay, I have brought this to the user@list I don’t think the negative pair should be omitted…..
if the score of all of the pairs are 1.0, the result will be worse…I have tried… Best Regards, Sendong Li > 在 2015年2月26日,下午10:07,Sean Owen <so...@cloudera.com> 写道: > > Yes, I mean, do not generate a Rating for these data points. What then? > > Also would you care to bring this to the user@ list? it's kind of interesting. > > On Thu, Feb 26, 2015 at 2:02 PM, lisendong <lisend...@163.com> wrote: >> I set the score of ‘0’ interaction user-item pair to 0.0 >> the code is as following: >> >> if (ifclick > 0) { >> score = 1.0; >> } >> else { >> score = 0.0; >> } >> return new Rating(user_id, photo_id, score); >> >> both method use the same ratings rdd >> >> because of the same random seed(1 in my case), the result is stable. >> >> >> Best Regards, >> Sendong Li >> >> >> 在 2015年2月26日,下午9:53,Sean Owen <so...@cloudera.com> 写道: >> >> >> I see why you say that, yes. >> >> Are you actually encoding the '0' interactions, or just omitting them? >> I think you should do the latter. >> >> Is the AUC stable over many runs or did you just run once? >> >> On Thu, Feb 26, 2015 at 1:42 PM, lisendong <lisend...@163.com> wrote: >> >> Hi meng, fotero, sowen: >> >> I’m using ALS with spark 1.0.0, the code should be: >> https://github.com/apache/spark/blob/branch-1.0/mllib/src/main/scala/org/apache/spark/mllib/recommendation/ALS.scala >> >> I think the following two method should produce the same (or near) result: >> >> MatrixFactorizationModel model = ALS.train(ratings.rdd(), 30, 30, 0.01, -1, >> 1); >> >> MatrixFactorizationModel model = ALS.trainImplicit(ratings.rdd(), 30, 30, >> 0.01, -1, 0, 1); >> >> the data I used is display log, the format of log is as following: >> >> user item if-click >> >> >> >> >> >> >> I use 1.0 as score for click pair, and 0 as score for non-click pair. >> >> in the second method, the alpha is set to zero, so the confidence for >> positive and negative are both 1.0 (right?) >> >> I think the two method should produce similar result, but the result is : >> the second method’s result is very bad (the AUC of the first result is 0.7, >> but the AUC of the second result is only 0.61) >> >> >> I could not understand why, could you help me? >> >> >> Thank you very much! >> >> Best Regards, >> Sendong Li >> >> --------------------------------------------------------------------- To unsubscribe, e-mail: user-unsubscr...@spark.apache.org For additional commands, e-mail: user-h...@spark.apache.org