New answers tagged nlp
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Manipulating noise to get some data in right format and apply it to task using PPO
From my understanding of your question, you are looking to implement a learning-to-sort algorithm.
There are current learning-to-sort machine learning solutions that do not require reinforcement ...
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What is the right Pytorch RNN implementation?
nn.Linear should already learn an additive bias by default.
This example implements RNN with no activation likely just for educational purposes, since that makes no ...
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Manipulating noise to get some data in right format and apply it to task using PPO
In terms of process optimization, RL is an excellent option but the environment definition and its policy could be difficult to implement.
That's why a genetic algorithm is a good alternative as it ...
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Range of values of BERT and other embeddings?
The values depend on the activation function, but I usually see very small positive values close to 0: this is probably due to the small probabilities between tokens.
You can see the behavior of the ...
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What are some methods to reduce a dataframe so I can pass it as one sample to an SVM?
SVM are not meant to solve "arbitrarily long" classification problem, therefore you have few choices:
use PCA for sequences, however it takes very long since it has to build a giant matrix ...
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What are some methods to reduce a dataframe so I can pass it as one sample to an SVM?
The standard is to take the mean across each sentence, leaving you with a vector for each participant. From there you can use t-SNE, UMAP or PCA to reduce the size of each vector.
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How to perform Grid Search on NLP CRF model
The code does produce an exception indeed, but it is catched by the try-except. To avoid the exception, you could modify your local copy of the sklearn_crfsuite library and add the missing attributes (...
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Model to implement Question Answering System over structured data
One efficient way is to use the roberta base squad 2 model, using your text as context and then ask questions.
It should work well and the model can be downloaded directly.
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Performing a text classification based on a dictionary
As defined, there's no ML in this problem: the program would associate each keyword to a category, so it would consist of a loop over the words in the documents, and inside the loop there is an if ...
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How to deal with spelling errors in NLP classfier (low resource language)
If the language doesn't have any spelling correction tool and you want to take care of spelling errors, practically you'd have to build one by using string similarity measures, and using frequency as ...
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BertTokenizer Loading Problem
It could be due to an internet connection issue, that's why it is always safer to download your model in a local folder first and then load it directly using the absolute path.
In addition to that ...
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Can I use Sentence-Bert to embed event triples?
Using triples could lead to wrong results because some headlines could contain double negations or other complex structures that are difficult to classify with triples.
However, you can apply directly ...
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How to perform entity level train-val-test split for NER task?
I know it's a bit late, but I had the same question and developed a method which is available here:
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LSTM basic doubt
First of all LSTM does not know the word it received, not at least in the sense that you think. LSTM like all neural net cell works with numeric vector representation. Even if you would build a ...
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NLP logistic regression
This is a completely plausible model. You have five features (probably one-hot encoded) and then a categorical outcome. This is a reasonable place to use a (multinomial) logistic regression.
Depending ...
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