On 2020-03-19 00:11, Praneet Singh wrote:
I am training a SGD Classifier with some training dataset which is
temporary and will be lost after sometime. So I am planning to save
the model in pickle file and reuse it and train again with some
another dataset that arrives. But It forgets the previously learned
data.
As far as I researched in google, tensorflow model allows transfer
learning and not forgetting the previous learning but is there any
other way with sklearn model to achieve this??
any help would be appreciated
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Did you use incremental estimator and partial _fit? If not, try to use
them. Should work.
Another option is to us deep learning and store the weights for the
first model and initialize the second model with that weight and keep
doing it for the rest of the models.
--
Best Regards,
Farzana Anowar,
PhD Candidate
Department of Computer Science
University of Regina
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