confidence = 1 + alpha * |rating| here (so, c1 means confidence - 1),
so alpha = 1 doesn't specially mean high confidence. The loss function
is computed over the whole input matrix, including all missing 0
entries. These have a minimal confidence of 1 according to this
formula. alpha controls how
It sounds like you're describing the explicit case, or any matrix
decomposition. Are you sure that's best for count-like data? It
depends, but my experience is that the implicit formulation is
better. In a way, the difference between 10,000 and 1,000 count is
less significant than the difference
In your experience with using implicit factorization for document
clustering, how did you tune alpha ? Using perplexity measures or just
something simple like 1 + rating since the ratings are always positive in
this case
On Sun, Jul 26, 2015 at 1:23 AM, Sean Owen so...@cloudera.com wrote:
I will think further but in the current implicit formulation with
confidence, looks like I am factorizing a 0/1 matrix with weights 1 +
alpha*rating for observed (1) values and 1 for unobserved (0) values. It's
a bit different from LSA model.
On Sun, Jul 26, 2015 at 6:45 AM, Debasish Das
Hi All,
I have a problem when writing streaming data to cassandra. Or existing
product is on Oracle DB in which while wrtiting data, locks are maintained
such that duplicates in the DB are avoided.
But as spark has parallel processing architecture, if more than 1 thread is
trying to write same
We got good clustering results from Implicit factorization using alpha =
1.0 since I thought to have a confidence of 1 + rating to observed entries
and 1 to unobserved entries. I used positivity / sparse coding basically to
force sparsity on document / topic matrix...But then I got confused
Thanks Patrick. I'll await resumption of the master tree's nightly builds.
-Bharath
On Fri, Jul 24, 2015 at 8:38 PM, Patrick Wendell pwend...@gmail.com wrote:
Hey Bharath,
There was actually an incompatible change to the build process that
broke several of the Jenkins builds. This should be
Simply customize your log4j confit instead of modifying code if you don't
want messages from that class.
Regards
Mridul
On Sunday, July 26, 2015, Sea 261810...@qq.com wrote:
This exception is so ugly!!! The screen is full of these information when
the program runs a long time, and they
If I read the code correctly, that error message came
from CoarseGrainedSchedulerBackend.
There may be existing / future error messages, other than the one cited
below, which are useful. Maybe change the log level of this message to
DEBUG ?
Cheers
On Sun, Jul 26, 2015 at 3:28 PM, Mridul
Given that 2.11 may be more stringent with respect to warnings, we might
consider building with 2.11 instead of 2.10 in the pull request builder.
This would also have some secondary benefits in terms of letting us use
tools like Scapegoat or SCoverage highlighting.
On Sat, Jul 25, 2015 at 8:52
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