Is there a PR or issue where GBT / RF progress in MLLib is tracked ?
2014-04-17 21:11 GMT+02:00 Evan R. Sparks evan.spa...@gmail.com:
Sorry - I meant to say that Multiclass classification, Gradient
Boosting, and Random Forest support based on the recent Decision Tree
implementation in MLlib
Hi Sparkers,
We have a Storm cluster and looking for a decent execution engine for
machine learned models. What I've seen from MLLib is extremely positive,
but we can't just throw away our Storm based stack.
So my question is: is it feasible/recommended to train models in
Spark/MLLib and execute
,
which at least provides an online lda.
C
On Thursday, June 19, 2014, Eustache DIEMERT eusta...@diemert.fr wrote:
Hi Sparkers,
We have a Storm cluster and looking for a decent execution engine for
machine learned models. What I've seen from MLLib is extremely positive,
but we can't just
learning.
On Thu, Jun 19, 2014 at 12:26 AM, Eustache DIEMERT eusta...@diemert.fr
wrote:
Hi Sparkers,
We have a Storm cluster and looking for a decent execution engine for
machine learned models. What I've seen from MLLib is extremely positive,
but we can't just throw away our Storm based stack
I'm interested in this topic too :)
Are the MLLib core devs on this list ?
E/
2014-06-24 14:19 GMT+02:00 holdingonrobin robinholdin...@gmail.com:
Anyone knows anything about it? Or should I actually move this topic to a
MLlib specif mailing list? Any information is appreciated! Thanks!
Hi list,
I'm benchmarking MLlib for a regression task [1] and get strange results.
Namely, using RidgeRegressionWithSGD it seems the predicted points miss the
intercept:
{code}
val trainedModel = RidgeRegressionWithSGD.train(trainingData, 1000)
...
valuesAndPreds.take(10).map(t = println(t))
Printing the model show the intercept is always 0 :(
Should I open a bug for that ?
2014-07-02 16:11 GMT+02:00 Eustache DIEMERT eusta...@diemert.fr:
Hi list,
I'm benchmarking MLlib for a regression task [1] and get strange results.
Namely, using RidgeRegressionWithSGD it seems
of
these regression algorithms, for example how to choose a good step and
number of iterations? I wonder if I'm using those right...
Thanks,
--
*Thomas ROBERT*
www.creativedata.fr
2014-07-03 16:16 GMT+02:00 Eustache DIEMERT eusta...@diemert.fr:
Printing the model show the intercept is always 0
+02:00 Eustache DIEMERT eusta...@diemert.fr:
Printing the model show the intercept is always 0 :(
Should I open a bug for that ?
2014-07-02 16:11 GMT+02:00 Eustache DIEMERT eusta...@diemert.fr:
Hi list,
I'm benchmarking MLlib for a regression task [1] and get strange
results.
Namely
the ones column.
Does anyone here has had success with this code on real-world datasets ?
[1] https://github.com/oddskool/mllib-samples/tree/ridge (in the ridge
branch)
2014-07-07 9:08 GMT+02:00 Eustache DIEMERT eusta...@diemert.fr:
Well, why not, but IMHO MLLib Logistic Regression is unusable
Wild guess maybe, but do you decode the json records in Python ? it could
be much slower as the default lib is quite slow.
If so try ujson [1] - a C implementation that is at least an order of
magnitude faster.
HTH
[1] https://pypi.python.org/pypi/ujson
2014-10-22 16:51 GMT+02:00 Marius
11 matches
Mail list logo