Personally, the most exciting additions that are coming to Mahout are
all the scala and spark bindings that are bringing linear algebra semantics.Far
too often, a canned algorithm never works as expected, and asdata scientists we
want to try out a bunch of algorithmic tweaks whichrequire getting into the
code. With these bindings, we can try outmore researchy stuff and have it
production ready.
Nilesh
On Tuesday, October 21, 2014 8:01 PM, Lee S <[email protected]> wrote:
As a developer, who is facing the library chosen between mahout and mllib,
I have some idea below.
Mahout has no any decision tree algorithm. But MLLIB has the components of
constructing a decision tree algorithm such as gini index, information
gain. And also I think mahout can add algorithm about frequency pattern
mining which is very import in feature selection and statistic analysis.
MLLIB has no frequent mining algorithms.
p.s Why fpgrowth algorithm is removed in version 0.9?
2014-10-22 9:12 GMT+08:00 Vibhanshu Prasad <[email protected]>:
> actually spark is available in python also, so users of spark are having an
> upper hand over users of traditional users of mahout. This is applicable to
> all the libraries of python (including numpy).
>
> On Wed, Oct 22, 2014 at 3:54 AM, Ted Dunning <[email protected]>
> wrote:
>
> > On Tue, Oct 21, 2014 at 3:04 PM, Mahesh Balija <
> [email protected]
> > >
> > wrote:
> >
> > > I am trying to differentiate between Mahout and Spark, here is the
> small
> > > list,
> > >
> > > Features Mahout Spark Clustering Y Y Classification Y Y
> Regression Y
> > > Y Dimensionality Reduction Y Y Java Y Y Scala N Y Python N Y
> Numpy N
> > > Y Hadoop Y Y Text Mining Y N Scala/Spark Bindings Y N/A
> scalability Y
> > > Y
> > >
> >
> > Mahout doesn't actually have strong features for clustering,
> classification
> > and regression. Mahout is very strong in recommendations (which you don't
> > mention) and dimensionality reduction.
> >
> > Mahout does support scala in the development version.
> >
> > What do you mean by support for Numpy?
> >
>
