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Softmax Classifier & partial training #307

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ElGigi opened this issue Sep 12, 2023 · 1 comment
Open

Softmax Classifier & partial training #307

ElGigi opened this issue Sep 12, 2023 · 1 comment
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@ElGigi
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ElGigi commented Sep 12, 2023

Hi,

In the documentation it is stated that partial training can be used to reduce memory consumption.

I tried to train a Softmax classifier with several datasets and partial methods.
But only the first labels of the train() method are known. If new labels are present in the dataset given to the partial() method, they are not taken into account.

Can Dataset object retain set of all labels after Labeled::fold() method?

Regards.

@andrewdalpino
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Yes, the first training set defines all the possible labels for the model. If you want to fold your dataset such that each fold has samples that correspond to all possible classes in the master dataset then you can use the straftifiedFold() method.

$folds = $dataset->stratifiedFold(5);

https://docs.rubixml.com/2.0/datasets/labeled.html#stratification

@andrewdalpino andrewdalpino added the question Further information is requested label Sep 13, 2023
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