ValueError: cannot compute mean with no input

[krishnarevi]

Does this model support german keywords? There is an issue when trying to fit the model with german keywords. Can you please suggest ?

[VMD7]

Regarding this issue you can remove the epochs field or your can give epoches more than 4. This might help to solve this issue.

[adri0]

I'm also getting this error when trying to run the code from Tim's article, Unsupervised Text Classification with Lbl2Vec

[jarolim14]

anyone found the source of the error?

[isaldiviagonzatti]

Same here, getting ` cannot compute mean with no input ' and no way to solve it. @krishnarevi is there any fix to this? what exactly is going on? Thanks

[isaldiviagonzatti]

Regarding this issue you can remove the epochs field or your can give epoches more than 4. This might help to solve this issue.

This does not work.

[1jamesthompson1]

I am also having this problem.

ValueError: cannot compute mean with no input

i can provide more information if wanted. But this is the model function

Lbl2Vec_model = Lbl2Vec(keywords_list=list(labels.keywords), tagged_documents=full_corpus['tagged_responses'][full_corpus['data_set_type'] == 'train'], label_names=list(labels.class_name), similarity_threshold=0.43, min_num_docs=5, epochs=10)

[shashankmc]

I am facing the same issue and after debugging I found that the problem arises here -

Lbl2Vec/lbl2vec/lbl2vec.py

Line 609 in d9efdf5

cleaned_keywords_list = list(

I always get a warning stating that the keywords_list are unknown to the Doc2Vec model and therefore will not be used to train. Which in result provides an empty cleaned_keywords_list and an empty keyword_vectors which is passed onto the methoddoc2vec_model.dv.most_similar from Doc2Vec class, there aren't any keyword_vectors, so mean value cannot be computed.

Only option I feel at this point that makes sense (which is also mentioned in the logger warning or info) - change your keywords to words that are present in the doc2vec model or train your own doc2vec model.