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From Denis Magda <dma...@apache.org>
Subject Re: Ignite ML withKeepBinary cache
Date Thu, 03 Jan 2019 19:46:19 GMT

Sounds like Ignite ML is a perfect fit for your task. Our ML expert will
help you to come up with a clean solution once the holidays season is over.

In general, will you be able to write a blog post on how Ignite ML is used
for your task once the issues are addressed?


On Wed, Jan 2, 2019 at 11:25 PM otorreno <oscar.torreno@shapelets.io> wrote:

> Denis,
> We have some metadata stored in an Ignite Cache where each row describes a
> certain data series, and each column is a property (could be actually of
> any
> type: strings, doubles, etc.). You can think about it as a table describing
> our data series. This table might be potentially quite big, given a high
> number of series and properties.
> Based on this table we would like to clusterize our data using different
> algorithms (e.g. k-means, decision tree).
> I started looking at it and I liked pretty much the way you have done the
> pre-processing pipeline for feature selection, transformation,
> normalization
> and scaling. The only stone I found on my way was the BinaryObject problem
> I
> mentioned.
> In fact I made it work as I described in my first post, but with a dirty
> solution as I didn't find the way to access the keepBinary property of the
> cache used as input. In any case, I will be glad to help in finding a clean
> solution to the problem if needed.
> Best,
> Oscar
> --
> Sent from: http://apache-ignite-developers.2346864.n4.nabble.com/

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