Collaborative-Filtering-recommendation | 电影评估推荐系统

 by   LunaBlack Python Version: Current License: No License

kandi X-RAY | Collaborative-Filtering-recommendation Summary

kandi X-RAY | Collaborative-Filtering-recommendation Summary

Collaborative-Filtering-recommendation is a Python library. Collaborative-Filtering-recommendation has no bugs, it has no vulnerabilities and it has low support. However Collaborative-Filtering-recommendation build file is not available. You can download it from GitHub.


            kandi-support Support

              Collaborative-Filtering-recommendation has a low active ecosystem.
              It has 16 star(s) with 3 fork(s). There are 1 watchers for this library.
              It had no major release in the last 6 months.
              Collaborative-Filtering-recommendation has no issues reported. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of Collaborative-Filtering-recommendation is current.

            kandi-Quality Quality

              Collaborative-Filtering-recommendation has 0 bugs and 0 code smells.

            kandi-Security Security

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

            kandi-License License

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

            kandi-Reuse Reuse

              Collaborative-Filtering-recommendation releases are not available. You will need to build from source code and install.
              Collaborative-Filtering-recommendation 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 Collaborative-Filtering-recommendation and discovered the below as its top functions. This is intended to give you an instant insight into Collaborative-Filtering-recommendation implemented functionality, and help decide if they suit your requirements.
            • Average 10 times
            • Calculate the average rating
            • Calculates the mean movie rating
            • Calculate movie rating
            • Get a list of k nearest neighbors
            • Given a list of movieRatings find the most common common users
            • Computes the similarity between two movies
            • Returns a list of k nearest neighbors with k nearest neighbors
            • Compute the similarity between two users
            • Find the most common movie in a list
            • Find k nearest neighbors
            • Calculates the CBMM rating
            • Compute the mean rating of a user
            • Function for CFMM rating prediction
            Get all kandi verified functions for this library.

            Collaborative-Filtering-recommendation Key Features

            No Key Features are available at this moment for Collaborative-Filtering-recommendation.

            Collaborative-Filtering-recommendation Examples and Code Snippets

            No Code Snippets are available at this moment for Collaborative-Filtering-recommendation.

            Community Discussions

            No Community Discussions are available at this moment for Collaborative-Filtering-recommendation.Refer to stack overflow page for discussions.

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


            No vulnerabilities reported

            Install Collaborative-Filtering-recommendation

            You can download it from GitHub.
            You can use Collaborative-Filtering-recommendation 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.


            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 .
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          • CLI

            gh repo clone LunaBlack/Collaborative-Filtering-recommendation

          • sshUrl


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