[scikit-learn] Questions about partial_fit and the Incremental library in Sci-kit learn

[Farzana Anowar]

On 2019-09-09 12:12, Daniel Sullivan wrote:
> Hi Farzana,
> 
> If I understand your question correctly you're asking how the SGD
> classifier works incrementally? The SGD algorithm maintains a single
> set of weights and iterates through all data points one at a time in a
> batch. It adjusts its weights on each iteration. So to answer your
> question, it trains on each instance, not on the batch. However, the
> algorithm can iterate multiple times through a single batch. Let me
> know if that answers your question.
> 
> Best,
> 
> Danny
> 
> On Mon, Sep 9, 2019 at 11:56 AM Farzana Anowar <fad469 at uregina.ca>
> wrote:
> 
>> Hello Sir/Madam,
>> 
>> I subscribed to the link you sent me.
>> 
>> I am posting my question again:
>> 
>> This Is Farzana Anowar, a Ph.D. candidate in University of Regina.
>> Currently, I'm working to develop a model that learns incrementally
>> from
>> non-stationary data. I have come across an Incremental library in
>> sci-kit learn that actually allows to do that using partial_fit. I
>> have
>> searched a lot for the detailed information about this 'incremental'
>> 
>> library and 'partial_fit', however, I couldn't find any.
>> 
>> It would be great if you could provide me with some detailed
>> information
>> about these two regarding how they actually work. For example, If we
>> 
>> take SGD as a classifier, the incremental library will allow me to
>> take
>> chunks/batches of data. My question is: Do this incremental library
>> train (using parial_fit) the whole batch at a time and then produce
>> a
>> classification performance or it takes a batch and trains each
>> instance
>> at a time from the batch.
>> 
>> Thanks in advance!
>> 
>> --
>> Regards,
>> 
>> Farzana Anowar
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-- 
Regards,

Farzana Anowar