Denis/Yury,
Upon review of your previous comments, please respond to my feedback :
1. I believe GA Grid can be implemented in separate package within ML
library and operate independently of other algorithms for use cases where
/only /GA is required.
2. I am still not totally clear concerning Trainer and Model relationship
in the ML API.
a. Am I correct that org.apache.ignite.ml.Trainer and
org.apache.ignite.ml.Model
API is not available as it is under development? Please advise.
b. Based on Yury's comments:
"...For both concepts we have API: org.apache.ignite.ml.Model and
org.apache.ignite.ml.Trainer. So if we want to use genetic algoritm for
model trainig we should implement specific trainer for each ML algorithms
like lin regression, kmean, decision tree and others.
For example let`s take a look on lin regression. Currently we have OLS
(Ordinary Least Squares) multiple linear regression. For this regression we
will have OLSRegressionModel and at least two possible trainers: analytical
trainer (a solution of matrix equation, analytical solution) and gradient
descent (numerical solution). And also we could implement GA trainer which
will use GA Grid... "
Do org.apache.ignite.ml.Trainer generate org.apache.ignite.ml.Models?
Please advise and clarify accordingly.
Best,
Turik
is an algorithm that generates
training algorithm builds a mode
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