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https://issues.apache.org/jira/browse/FLINK-2116?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14572481#comment-14572481
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Mikio Braun commented on FLINK-2116:
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I think if you look at MultipleLinearRegression, the code is now much better
because you can focus much better on the kind of prediction you want to
compute. One comment here, allowing to make predictions only for one element at
a time might be less efficient than doing the prediction for a set of elements
which can often be written down in matrix algebra. But that probably doesn't
fit into the Flink framework as well.
On the other hand, the whole Predictor/implicit business is still incredibly
noise in terms of boilerplate code. That's probably a personal perference, but
when you spend 10 out of 15 lines on setting up stuff for the compiler's type
system, I get the feeling that this is not the right way to do it. I understand
how it works, and all, of course, but still... . Maybe using shorter variable
names for the type parameters would work, I don't know.
> Make pipeline extension require less coding
> -------------------------------------------
>
> Key: FLINK-2116
> URL: https://issues.apache.org/jira/browse/FLINK-2116
> Project: Flink
> Issue Type: Improvement
> Components: Machine Learning Library
> Reporter: Mikio Braun
> Assignee: Till Rohrmann
> Priority: Minor
>
> Right now, implementing methods from the pipelines for new types, or even
> adding new methods to pipelines requires many steps:
> 1) implementing methods for new types
> implement implicit of the corresponding class encapsulating the operation
> in the companion object
> 2) adding methods to the pipeline
> - adding a method
> - adding a trait for the operation
> - implement implicit in the companion object
> These are all objects which contain many generic parameters, so reducing the
> work would be great.
> The goal should be that you can really focus on the code to add, and have as
> little boilerplate code as possible.
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