See https://builds.apache.org/job/Mahout-Quality/2073/changes
Changes:
[jmannix] Fixes MAHOUT-1147. Just had to set the MODEL_PATHS on the doc-topic
inference job
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Hudson commented on MAHOUT-1147:
Integrated in Mahout-Quality #2073 (See
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Ted Dunning commented on MAHOUT-975:
If you see a significant, low-effort improvement,
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Ted Dunning updated MAHOUT-975:
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Fix Version/s: (was: 0.8)
Backlog
Bug in Gradient Machine - Computation
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Grant Ingersoll updated MAHOUT-1030:
Fix Version/s: (was: 0.8)
1.0
I'm going to push this. I know that
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Grant Ingersoll commented on MAHOUT-1214:
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Any update on this for applying
I pushed M-1030 and M-1233. If we can get M-833 and M-1214 in by Thursday, I
can roll an RC on Thursday.
-Grant
On Jun 11, 2013, at 8:56 AM, Grant Ingersoll gsing...@apache.org wrote:
Down to 4 issues! I would say what they are, but JIRA is flaking out again.
My instinct is that 1030 and
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Grant Ingersoll updated MAHOUT-1030:
Fix Version/s: 0.9
Regression: Clustered Points Should be
Grant,
M-1030: This was caused as a result of the refactoring of the clustering code
post 0.7 release. I feel we will be cutting close by rushing this for 0.8, I
suggest that we defer this to backlog (or next release).
Suneel
From: Grant Ingersoll
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Grant Ingersoll resolved MAHOUT-1233.
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Resolution: Incomplete
Please reopen if you have a repeatable test case, as I am not
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Yiqun Hu commented on MAHOUT-1214:
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The example has been verified but not as a junit
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Yiqun Hu commented on MAHOUT-1214:
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According to the 3 feedbacks from Robin, we are
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Yexi Jiang commented on MAHOUT-975:
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There are multiple problems (not only bugs) with
congratulations!
On Mon, Jun 10, 2013 at 10:22 PM, Dan Filimon
dangeorge.fili...@gmail.comwrote:
Congratulations to the both of you! :)
It's great to have you on board!
On Tue, Jun 11, 2013 at 3:58 AM, Stevo Slavić ssla...@gmail.com wrote:
Thanks Grant, Suneel and rest of the team,
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Ted Dunning commented on MAHOUT-975:
{quote}
1) The GradientMachine is a special case
Dan Filimon created MAHOUT-1253:
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Summary: Add experiment tools for StreamingKMeans
Key: MAHOUT-1253
URL: https://issues.apache.org/jira/browse/MAHOUT-1253
Project: Mahout
Issue Type:
Dan Filimon created MAHOUT-1254:
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Summary: Final round of cleanup for StreamingKMeans
Key: MAHOUT-1254
URL: https://issues.apache.org/jira/browse/MAHOUT-1254
Project: Mahout
Issue Type:
Dan Filimon created MAHOUT-1255:
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Summary: Change BallKMeans weighting to use log(weight)
Key: MAHOUT-1255
URL: https://issues.apache.org/jira/browse/MAHOUT-1255
Project: Mahout
Issue Type:
Dan Filimon created MAHOUT-1256:
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Summary: Improve the CSV handling code to get vectors
Key: MAHOUT-1256
URL: https://issues.apache.org/jira/browse/MAHOUT-1256
Project: Mahout
Issue Type:
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Ted Dunning commented on MAHOUT-1255:
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I know how the testing inspired this change,
Sorry to rain on everyone's party, but I opened a few more issues I need to
take of before 0.8 final that I had forgotten about.
M-1253 to M-1256.
I have code for all of these (that I tested, incidentally, that's the code
I used for the experiments in the talk :), just need to merge it in and I
abt review: you can send it my way
Robin Anil | Software Engineer | +1 312 869 2602 | Google Inc.
On Tue, Jun 11, 2013 at 3:36 PM, Dan Filimon dangeorge.fili...@gmail.comwrote:
Sorry to rain on everyone's party, but I opened a few more issues I need to
take of before 0.8 final that I had
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Robin Anil commented on MAHOUT-1253:
Please also add it to the the
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Yexi Jiang commented on MAHOUT-975:
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The size of goodLabels in updateRanking is always 1
See https://builds.apache.org/job/Mahout-Quality/2074/
See
https://builds.apache.org/job/mahout-nightly/org.apache.mahout$mahout-integration/1259/
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[INFO]
[INFO]
See https://builds.apache.org/job/mahout-nightly/1259/changes
Changes:
[jmannix] Fixes MAHOUT-1147. Just had to set the MODEL_PATHS on the doc-topic
inference job
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Downloading:
Hi folks,
I'm trying to use mahout's PCA implementation based on SSVD in our
application. I understand that in order to avoid densifying the sparse
input, mahout provides an option that the mean of cols can be a parameters
to pass into the algorithms. However, a lot of time, the scale of each
Hi,
Recently we started to use the in-mapper combiner design patterns in
our hadoop based algorithms at Alpine Data Labs; those algorithms
include variable selection using info gain, decision tree, naive bayes
model and SVM, and we found that we can have 20~40% performance
speedup without doing
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Paul R. Brown commented on MAHOUT-1175:
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FWIW, I'm experiencing the same issues
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