TopicModeling | Topic Modeling using Latent Dirichlet Allocation and Non | Topic Modeling library

 by   abhisharma7 Python Version: Current License: MIT

kandi X-RAY | TopicModeling Summary

kandi X-RAY | TopicModeling Summary

TopicModeling is a Python library typically used in Artificial Intelligence, Topic Modeling applications. TopicModeling has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However TopicModeling build file is not available. You can download it from GitHub.

Topic Modeling using Latent Dirichlet Allocation and Non Negative Matrix Factorization
Support
    Quality
      Security
        License
          Reuse

            kandi-support Support

              TopicModeling has a low active ecosystem.
              It has 1 star(s) with 0 fork(s). There are 2 watchers for this library.
              OutlinedDot
              It had no major release in the last 6 months.
              TopicModeling has no issues reported. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of TopicModeling is current.

            kandi-Quality Quality

              TopicModeling has 0 bugs and 0 code smells.

            kandi-Security Security

              TopicModeling has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              TopicModeling code analysis shows 0 unresolved vulnerabilities.
              There are 0 security hotspots that need review.

            kandi-License License

              TopicModeling is licensed under the MIT License. This license is Permissive.
              Permissive licenses have the least restrictions, and you can use them in most projects.

            kandi-Reuse Reuse

              TopicModeling releases are not available. You will need to build from source code and install.
              TopicModeling has no build file. You will be need to create the build yourself to build the component from source.

            Top functions reviewed by kandi - BETA

            kandi has reviewed TopicModeling and discovered the below as its top functions. This is intended to give you an instant insight into TopicModeling implemented functionality, and help decide if they suit your requirements.
            • Construct TFIDF vectorizer .
            • Create a count vectorizer .
            • Displays the list of topics .
            Get all kandi verified functions for this library.

            TopicModeling Key Features

            No Key Features are available at this moment for TopicModeling.

            TopicModeling Examples and Code Snippets

            No Code Snippets are available at this moment for TopicModeling.

            Community Discussions

            QUESTION

            Topic Modeling: graphical representation of words with the greatest differences between two topics
            Asked 2020-Mar-02 at 21:36

            In Text Mining with R, methods for unsupervised classification of documents, such as blog posts or news articles, are introduced. This is work for topic modeling. I'm running the codes enclosed in this link, but I do not know how obtain Figure 6.3, "Words with the greatest difference in beta between topic 2 and topic 1".

            Any suggestions please?

            ...

            ANSWER

            Answered 2020-Mar-02 at 21:36

            This book has source available, you can just click the edit button and be taken to the GitHub project with the current page to edit. Just navigate to the chapter that you need (a Rmd file) and look for the text closest to the image.

            Thankfully this image was also made with R, so you can just check: here

            Posting for completeness:

            Source https://stackoverflow.com/questions/60496730

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

            Vulnerabilities

            No vulnerabilities reported

            Install TopicModeling

            You can download it from GitHub.
            You can use TopicModeling like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

            Support

            For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .
            Find more information at:

            Find, review, and download reusable Libraries, Code Snippets, Cloud APIs from over 650 million Knowledge Items

            Find more libraries
            CLONE
          • HTTPS

            https://github.com/abhisharma7/TopicModeling.git

          • CLI

            gh repo clone abhisharma7/TopicModeling

          • sshUrl

            git@github.com:abhisharma7/TopicModeling.git

          • Stay Updated

            Subscribe to our newsletter for trending solutions and developer bootcamps

            Agree to Sign up and Terms & Conditions

            Share this Page

            share link

            Consider Popular Topic Modeling Libraries

            gensim

            by RaRe-Technologies

            Familia

            by baidu

            BERTopic

            by MaartenGr

            Top2Vec

            by ddangelov

            lda

            by lda-project

            Try Top Libraries by abhisharma7

            WiscKey

            by abhisharma7C++

            FacePoseEstimation

            by abhisharma7Python

            Computer-Network

            by abhisharma7Python

            Machine-Learning

            by abhisharma7Python

            Web-Crawling

            by abhisharma7Python