BERTopic
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MaartenGr
Leveraging BERT and c-TF-IDF to create easily interpretable topics.
Hi, I was just wondering if I am able to delete a specific topic from my model, or would I have to reduce it using the existing methods. Thanks
## **Highlights**: * Online/incremental topic modeling with `.partial_fit` * Expose c-TF-IDF model for customization with `bertopic.vectorizers.CTfidfTransformer` * Several parameters were added for potentially improved representations * `bm25_weighting` * `reduce_frequent_words` *...
The BerTopic model resulted the below Topics:  As you can see from the above, the model is finetuned to generate lesser outliers '-1' which has the count of 3...
My Bertopic result has too specific and too many clusters. Is there any way to increase the variance of the clusters? I understand that a high value for min_sample will...
I created the following dataframe from the model output ``` topics, probs = model.fit_transform(vic_msg) topic_df = model.get_topic_info() ``` And then I created another dataframe which consist of my messages, the...
Hello, Thank you for this fantastic work, Bertopic is really useful. I was wondering why is the visualization of the hierarchy based off the results of the c_tf_idf ? Since...
Hi, I am trying to use a custom model which I did additional training on, uploaded it to huggingface and having some problems. Right now I'm using the code snippet...
Hello, I am new to BERTopic and I'm trying to replace my old algorithms (Corex and LDA) with BERTopic. Here is my problem: I have many unlabeled documents (about 7000)....
Hello Maarten, first of all thank you so much for developing such an awesome project! I am currently running into an issue. When I use fit_transform function on a dataset,...
Hi Maarten, I've been using BERTopic for a while and it's an amazing resource! Thank you for all your hard work. I'm wondering if you can help me with an...
