topic_modeling | Topic Modeling using LDA and NMF in Python | Topic Modeling library

 by   ravishchawla HTML Version: Current License: No License

kandi X-RAY | topic_modeling Summary

kandi X-RAY | topic_modeling Summary

topic_modeling is a HTML library typically used in Artificial Intelligence, Topic Modeling applications. topic_modeling has no bugs, it has no vulnerabilities and it has low support. You can download it from GitHub.

Topic Modeling using LDA and NMF in Python The code on this repository corresponds to a Medium Blog Post: This repository covers implementation of LDA and NMF on the ABC Million News Headlines dataset.
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              topic_modeling has a low active ecosystem.
              It has 10 star(s) with 9 fork(s). There are 1 watchers for this library.
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              It had no major release in the last 6 months.
              topic_modeling has no issues reported. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of topic_modeling is current.

            kandi-Quality Quality

              topic_modeling has no bugs reported.

            kandi-Security Security

              topic_modeling has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

            kandi-License License

              topic_modeling does not have a standard license declared.
              Check the repository for any license declaration and review the terms closely.
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              Without a license, all rights are reserved, and you cannot use the library in your applications.

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              topic_modeling releases are not available. You will need to build from source code and install.

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            topic_modeling Key Features

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            topic_modeling Examples and Code Snippets

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            Community Discussions

            QUESTION

            text2vec's vocab_vectorizer ouput is the function itself
            Asked 2020-May-22 at 15:30

            I am trying to run through text2vec's example on this page. However, whenever I try to see what the vocab_vectorizer function returned, it's just an output of the function itself. In all my years of R coding, I've never seen this before, but it also feels funky enough to extend beyond just this function. Any pointers?

            ...

            ANSWER

            Answered 2020-May-22 at 15:30

            The output of vocab_vectorizer is supposed to be a function. I ran the function from the example in the documentation as below:

            Source https://stackoverflow.com/questions/61956502

            QUESTION

            Why do fit_transform and transform produce different results?
            Asked 2019-Jul-17 at 06:31

            I was playing around with LDA in the text2vec package and was confused why the fit_transfrom and transform were different when using the same data.

            The documentation states that transform applys the learned model to new data but the result is a lot different than the one produced from fit_transform

            ...

            ANSWER

            Answered 2019-Jul-17 at 06:31

            Good question! Indeed there is an issue with CRAN version (and it mostly fixed in dev version on github). The issue is following:

            1. During fit_transform we learn both document-topic distribution and word-topic distribution. Once converged we save word-topic inside the model and return document-topic as result.
            2. During transform we use fixed word-topic distribution and only infer document-topic. There is no guarantee that inferred document-topic will be the same and during fit_transform (but it should be close enough).

            What we've changed in dev version - we run fit_transform and transform in order to have almost same document-topic distribution for each methods. (there are couple additional parameter tweaks in order to make sure they are exactly the same - see documentation for development version).

            Source https://stackoverflow.com/questions/57063414

            QUESTION

            UnicodeDecodeError with processing a csv
            Asked 2019-May-15 at 17:16

            Suddently a "UnicodeDecodeError" arises in a code of mine which worked yesterday.

            File "D:\Anaconda\lib\site-packages\IPython\core\interactiveshell.py", line 3284, in run_code self.showtraceback(running_compiled_code=True)

            File "D:\Anaconda\lib\site-packages\IPython\core\interactiveshell.py", line 2021, in showtraceback value, tb, tb_offset=tb_offset)

            File "D:\Anaconda\lib\site-packages\IPython\core\ultratb.py", line 1379, in structured_traceback self, etype, value, tb, tb_offset, number_of_lines_of_context)

            File "D:\Anaconda\lib\site-packages\IPython\core\ultratb.py", line 1291, in structured_traceback elist = self._extract_tb(tb)

            File "D:\Anaconda\lib\site-packages\IPython\core\ultratb.py", line 1272, in _extract_tb return traceback.extract_tb(tb)

            File "D:\Anaconda\lib\traceback.py", line 72, in extract_tb return StackSummary.extract(walk_tb(tb), limit=limit)

            File "D:\Anaconda\lib\traceback.py", line 364, in extract f.line

            File "D:\Anaconda\lib\traceback.py", line 286, in line self._line = linecache.getline(self.filename, self.lineno).strip()

            File "D:\Anaconda\lib\linecache.py", line 16, in getline lines = getlines(filename, module_globals)

            File "D:\Anaconda\lib\linecache.py", line 47, in getlines return updatecache(filename, module_globals)

            File "D:\Anaconda\lib\linecache.py", line 137, in updatecache lines = fp.readlines()

            File "D:\Anaconda\lib\codecs.py", line 321, in decode (result, consumed) = self._buffer_decode(data, self.errors, final)

            UnicodeDecodeError: 'utf-8' codec can't decode byte 0xf6 in position 2441: invalid start byte

            ...

            ANSWER

            Answered 2019-May-15 at 17:16

            Without seeing the what's at position 2441 I'm not entirely sure, but it is probably one of the following:

            • A special, non-ascii/extended ascii character, in which case do the_string.encode("UTF-8") or when opening do encoding = "UTF-8" in the open function
            • You have \u or \U somewhere and this makes the next characters read as part of a Unicode sequence so do repr(the_string) to add backslashes to nullify backslashes after (Probably not this one)
            • You are reading a bytes object not a str object. Try opening it with r+b (read & write, bytes) in the open function

            I've more or less thrown spaghetti at a wall but I hope this helps!

            Source https://stackoverflow.com/questions/56153706

            Community Discussions, Code Snippets contain sources that include Stack Exchange Network

            Vulnerabilities

            No vulnerabilities reported

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