Any thoughts of this ?
On Sat, Jan 26, 2013 at 10:55 AM, Zia mel ziad.kame...@gmail.com wrote:
OK , in the precison when we reduce the size of sample to .1 or 0.05 ,
would the results be related when we check with all the data ? For
example, if we have data1 and data2 and test them using 0.1
Impossible to say. More data means a more reliable estimate all else equal.
That's about it.
On Jan 28, 2013 5:17 PM, Zia mel ziad.kame...@gmail.com wrote:
Any thoughts of this ?
On Sat, Jan 26, 2013 at 10:55 AM, Zia mel ziad.kame...@gmail.com wrote:
OK , in the precison when we reduce the
What about running several tests on small data , can't that give an
indicator of how big data will perform ?
Thanks
On Mon, Jan 28, 2013 at 11:19 AM, Sean Owen sro...@gmail.com wrote:
Impossible to say. More data means a more reliable estimate all else equal.
That's about it.
On Jan 28, 2013
Yes several independent samples of all the data will, together, give
you a better estimate of the real metric value than any individual
one.
On Mon, Jan 28, 2013 at 5:41 PM, Zia mel ziad.kame...@gmail.com wrote:
What about running several tests on small data , can't that give an
indicator of
The way I do it is to set x different for each user, to the number of
items in the user's test set -- you ask for x recommendations.
This makes precision == recall, note. It dodges this problem though.
Otherwise, if you fix x, the condition you need is stronger, really:
each user needs = x *test
Interesting. Using
IRStatistics stats = evaluator.evaluate(recommenderBuilder,
null, model, null, 5,
GenericRecommenderIRStatsEvaluator.CHOOSE_THRESHOLD,
1.0);
Can it be adjusted to each user ? In other
No, it takes a fixed at value. You can modify it to do whatever you want.
You will see it doesn't bother with users with little data, like
2*at data points.
On Fri, Jan 25, 2013 at 6:23 PM, Zia mel ziad.kame...@gmail.com wrote:
Interesting. Using
IRStatistics stats =
