Hi
>> Note: You cannot easily just use java.util.BitSet as you wish to
have
access to the underlying long[] to store the chromosome to enable efficient
crossover.
--Thanks for pointing this. However, I have considered few constraints
while doing the implementation.
1) I extended the existing class AbstractListChromosome, which
requires a Generic type. This is the reason for using a list of Long.
However, I can extend the Chromosome and use an array of primitive long.
BitSet also uses a similar data structure.
2) One problem of BitSet is the use of MSB to retain bits. As a
result, we won't be able to use the static utility methods of wrapper
classes(Long) for conversion between primitive type and string. We will
have to write custom code for conversion between string and integral types.
This is the only reason I have used BLOCKSIZE as 63 instead of 64.
>>// This is not actually required...
// int bit = cross & 64; // i.e. cross % 64
--Do you mean bit index is not required to calculate? How can we handle
crossover indexes which are not multiple of 64.
>> Do you think that allele sets other than binary would be useful to
implement? [IIUC your document above, it seems not (?).]
--The document only describes the data structure related to Binary
genotype. We already have an implementation of RandomKey genotype in
commons. We can think of adding other genotypes gradually.
Thanks & Regards
--Avijit Basak
On Sat, 1 May 2021 at 22:18, Gilles Sadowski <gillese...@gmail.com> wrote:
> Le ven. 30 avr. 2021 à 17:40, Avijit Basak <avijit.ba...@gmail.com> a
> écrit :
> >
> > Hi
> >
> > >>lot of spurious references to "Commons Numbers"
> > --I have only created the basic project structure. Changes
> > need to be made. Can anyone from the existing commons team help in doing
> > this.
>
> Wel, you should "search and replace":
> "Numbers" -> "Machine Learning"
> commons-numbers -> commons-machinelearning
>
> Other things (repository URL, JIRA project name and URL) require that
> a component be created (vote is pending).
> [As long as those files are not part of a PR, it is not urgent to fix
> them.]
>
> > >> For sure, populate it with the code extracted from CM's
> > "genetics"
> > package and proceed with the enhancements.
> > At first, I'd suggest to refactor the layout of the package (i.e. create
> > a "subpackage" for each component of a genetic algorithm).
> > -- I am working on it.
>
> Great!
>
> > Did not commit the code till now.
>
> OK. When you do, please ask for review on the "dev" ML.
>
> > >> Then some examination of the data-structures is required (a
> > binary chromosome is currently stored as a "List<Integer>").
> > -- I have recently done some work on this. Could you please
> > check this article and share your thought.
> > "*https://arxiv.org/abs/2103.04751
> > <https://arxiv.org/abs/2103.04751>*"
>
> Alex already provided a thorough response.
> It's a pity that JDK's BitSet is missing a few methods (e.g. "append")
> for a readily usable implementation of a "binary chromosome".
>
> Do you think that allele sets other than binary would be useful to
> implement? [IIUC your document above, it seems not (?).]
>
> > Are we thinking to use Spark for our parallelism
>
> No, if the code is to reside in Commons.
>
> > or a simple
> > multi-threading of Java.
>
> Yes, we'd depend only on JDK classes.
>
> > I would prefer to use java multi-threading and
> > avoid any other framework.
> > In java we don't have any library which can be used for AI/ML
> > programming with a very minimal learning curve. Can we think of
> fulfilling
> > this need?
>
> That would be nice. Don't hesitate to enlist fellow programmers. :-)
>
> Regards,
> Gilles
>
> > This will be helpful for many java developers to venture into
> > AI/ML without learning a new language like Python.
> >
> >
> >>> [...]
>
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>
--
Avijit Basak
