Taner,
It seems to have tf-idf vectors later, you need to create tf vectors
(DictionaryVectorizer.createTermFrequencyVectors) with logNormalize option
set to false, and normPower option set to -1.0f. This applies to
HighDFWordsPruner.pruneVectors, too.
I believe that solves your problem.
Best
I've been looking at examples of recommenders with an eye to reverse
engineering what's good and bad. Hard to say with any certainty, of course.
Netflix: has a bunch of different recommendation lists, some personalized, some
based on different forms of popularity or item similarity. The one
Hi Pablo,
Look in the CDBw unit tests for examples of invoking it from Java code.
Jeff
On Sep 6, 2013, at 5:56 PM, Pablo Andretta Jaskowiak pajaskow...@gmail.com
wrote:
Hello,
I'm trying to use the CDBw implementation from Mahout. Given that I
have a dataset in CSV format and a
Thanks Sebastian.
On Sat, Sep 7, 2013 at 8:24 PM, Sebastian Schelter
ssc.o...@googlemail.com wrote:
IIRC the algorithm behind ParallelSGDFactorizer needs shared memory,
which is not given in a shared-nothing environment.
On 07.09.2013 19:08, Tevfik Aytekin wrote:
Hi,
There seems to be no
