Machine Learning algorithm implementation

[María José Basgall]

Hi all,
I am a doctorate student in Computer Science and we are developing a
Self-Organizing Map (SOM) algorithm on MapReduce. I want to know about what
ML algorithm implementation is missing, because we want to make a
contribution to this project.
We checked out this page: https://mahout.apache.org/user
s/basics/algorithms.html and we figured out that the most of algorithms in
the MapReduce column are deprecated, what is the reason for it? Do we need
to think in Spark instead of MapReduce implementations?

Thanks,
MJ

[Dmitriy Lyubimov]

We primarily think in platform-independent, R-like way now.
http://mahout.apache.org/users/sparkbindings/home.html

We hope it should be a good news for algebraic algorithm implementers like
you.

Samsara is mapped into spark, flink and H20 as it stands (no mapreduce, you
are correct in that).

We recognize that the existing set of optimized algebra operators may not
always be enough, and so we expect that some part of an algorithm can be
done for a particular backend, but we usually hope it is abstracted enough
so that non-samsara parts can then be ported to other backends if need be.

-d

Post by María José Basgall
Hi all,
I am a doctorate student in Computer Science and we are developing a
Self-Organizing Map (SOM) algorithm on MapReduce. I want to know about what
ML algorithm implementation is missing, because we want to make a
contribution to this project.
We checked out this page: https://mahout.apache.org/user
s/basics/algorithms.html and we figured out that the most of algorithms in
the MapReduce column are deprecated, what is the reason for it? Do we need
to think in Spark instead of MapReduce implementations?
Thanks,
MJ