Ignite ML - Weka integration?

[joseheitor <jo...@heitorprojects.com>]

Hi Ignite-ML Team,

I have recently discovered WEKA - a Java ML workbench and library from the
University of Waikato.

I have observed that Ignite-ML is developing quickly in it's computational
capabilities, but is lacking a 'workbench environment' for interactive
data-science workflows. Surprisingly, I discovered an online Paper (from
2016:  here
<http://rdquest.com/wp-content/uploads/2016/07/Ignite-ML-Report.docx>  ),
which describes Apache Ignite's early ML implementation, to be rooted in the
WEKA ML library.

My question is thus: Is there any possibility in exploring an integration
between Ignite-ML and WEKA's workbench? (It would be great to leverage
WEKA's interactive exploratory, visualization and workflow capabilities with
Ignite-ML's distributed computational capabilities...)

Or is this concept completely irrational and impractical?

Looking forward to feedback from the talented Ignite-ML gurus!

Thanks,
Jose



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Re: Ignite ML - Weka integration?

[joseheitor <jo...@heitorprojects.com>]

Hi,

You also raise some interesting points...

Weka has integrations to Hadoop and Spark via 'plugins' from their package
manager. And Weka's 'sister-project', MOA is specifically intended to
operate on large data streams. These products are extensive, open-source and
extendible.

Regarding Python Notebooks - we can work with Weka's library in Python or
even Java in Notebooks (
https://waikato.github.io/weka-wiki/jupyter_notebooks/
<https://waikato.github.io/weka-wiki/jupyter_notebooks/>  ). I have played a
little with this and it works great.

I also wondered whether a workbench for Ignite ML would maybe be better
integrated into the Ignite Web Console. But looking at the extent of work
required to provide the kind of functionality and visualization already
available in Weka - one wonders if it isn't more rational to work on
integration between the projects? Weka, being a Java application is of
course also capable of running on any platform that Java supports, so it has
great portability.

I think that the work that the Ignite team are doing on ML is based on the
excellent concept of DML (distributed machine learning), which is extremely
important for future scalability. And it seems to have good momentum as seen
by the number of features being added to the new, upcoming 2.8 release. All
the development so far has understandably been focused on the underlying ML
'infrastructure'. The challenge though is that in order to stimulate
adoption, we need practical interactive environments.

Really looking forward to the evolution of ML on Ignite. And Kudos to the
talented team behind it.

Cheers,
Jose



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Re: Ignite ML - Weka integration?

[zaleslaw <za...@gmail.com>]

Hi! It's a good question and note about integration.
We have no this integration on roadmap, but I agree, that we have no good
'workbench environment'.
But should it be a kind of destop workbench or something else? I don't know.

I don't any examples of integration with the Weka for another distributed ML
tools like H2O or Spark ML.

I think that we could have more effort if we will have integration with the
Python Notebooks, Matplotlib or Apache Zeppelin that are widely used with
the tools mentioned above.

In my opinion, the Ignite ML is not the right choice for the everyday data
science operations, it has a limited support of dataframes (due to limited
support of SQL and so on)

P.S. I'd like Weka and used it for many years



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