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I just sketched out a supervised LDA step for some research that I would be happy to contribute. I think I'd need to do a little bit of plumbing re-routing, but the core bits are in place I believe. L…
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Anyone playing with any implementations of sLDA within gensim?
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Using class label:
concatenate every doc in one class, calculate word distribution, save as one topic.
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Hello @burbma ,
I am working with Pang review dataset to understand the working of sLDA. I am curious about how to print the inferred topics after fitting.
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I need help understanding how to implement the approach presented in
https://www.aimspress.com/article/doi/10.3934/mbe.2020192?viewType=HTML
In Table 1, the authors suggest an initial LDA training…
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#### Description
We want to compare gensim and [SageMaker](https://aws.amazon.com/ru/sagemaker/):
- LSI (after #1896) vs [SageMaker PCA](https://docs.aws.amazon.com/sagemaker/latest/dg/pca.html)
…
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Labelled LDA is a "topic-model"-ish algorithm similar to LDA, except that it's supervised. You give it some labels and documents with those labels, and it models the words that are in each of the labe…
ghost updated
2 years ago
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```
Add more examples documenting:
- How to create features in HCRFs;
- How to learn HMMs using supervised learning;
- Add samples on how to use LocalBinaryPatterns, Histogram of Oriented Gradient…
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```
Add more examples documenting:
- How to create features in HCRFs;
- How to learn HMMs using supervised learning;
- Add samples on how to use LocalBinaryPatterns, Histogram of Oriented Gradient…
-
```
Add more examples documenting:
- How to create features in HCRFs;
- How to learn HMMs using supervised learning;
- Add samples on how to use LocalBinaryPatterns, Histogram of Oriented Gradient…