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From Denis Magda <dma...@apache.org>
Subject Re: GA Grid: Request to contribute GA library to Apache Ignite
Date Tue, 07 Nov 2017 20:48:23 GMT
Yury,

Please see inline

> On Nov 7, 2017, at 12:11 PM, Yury Babak <y.chief@gmail.com> wrote:
> 
> Denis,
> 
> Let me clarify.
> 
> Firstly, here gene is a single model coefficient(neuron weight, etc),
> chromosomes - whole model representation.
> 

Sounds good. Actually a chromosome can be see as a model.

> Secondly GA should be implementation of Trainer API for each ML algorithm
> such as regression, clusterization, NNs, etc.
> 

It’s optional, right? Initially there should be a way to run standard operations over chromosomes
specific to GA only. Those operations/algorithms are crossover, fitness score, mutations.
Do this 3 operations fit trainer API? We’re putting aside extended support of regression,
clusterization, etc.

> And last but not least genetic algorithm does not fits for to Model API, so
> it shouldn't`t implement it. Generally genetic algorithm dont produce any
> predictive models.
> 

I’m a bit confused here. Before we say that a chromosome is a model in terms of ML and it’s
all about providing concrete trainer implementations. 

—
Denis

> Regards,
> Yury
> 
> 
> 
> --
> Sent from: http://apache-ignite-developers.2346864.n4.nabble.com/


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