BigARTM for semi-supervised learning

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juliaserebr

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Jul 4, 2018, 11:13:33 AM7/4/18
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Hi,

A part of my data is labeled and I am trying to use BigARTM for classification. If I understand correctly, I should use LabelRegularizationPhiRegularizer, but there is no documentation or examples for it. Do you have any tutorials or documentation for python interface?

Thank you,
Julia

Oleksandr Frei

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Jul 4, 2018, 11:40:21 AM7/4/18
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Hi,

BigARTM classification is fairly simple feature, but unfortunately there is no tutorial.

Basically, you need to set predict_class_id argument in artm.transform:
  • predict_class_id (str) – class_id of a target modality to predict. When this option is enabled the resulting columns of theta matrix will correspond to unique labels of a target modality. The values will represent p(c|d), which give the probability of class label c for document d.
More details about classification are here:
http://www.machinelearning.ru/wiki/images/d/da/Voron17fast.pdf (setionc IX.B - Multimodal ARTM / The class modality)
First you need to infer topics for a given document. Later, you use
Inline image 1
to find distribution on classification labels. Then for hard classification you take argmax - e.i class with highest p(c|d').

Kind regards,
Alex

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Мурат Апишев

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Jul 4, 2018, 11:57:40 AM7/4/18
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Hi!
 


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С уважением, Мурат Апишев.
 
Regards, Murat Apishev.



04.07.2018, 18:13, "juliaserebr" <julia...@gmail.com>:
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juliaserebr

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Jul 4, 2018, 12:11:44 PM7/4/18
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Alex, Murat,

Thank you so much!

Kind regards,
Julia

среда, 4 июля 2018 г., 18:13:33 UTC+3 пользователь juliaserebr написал:
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