knn-python | nearest neighbors classifier algorithm implementation

by mx0c Python Version: Current License: No License

X-Ray Key Features Code Snippets Community Discussions Vulnerabilities Install Support

kandi X-RAY | knn-python Summary

knn-python is a Python library. knn-python has no bugs, it has no vulnerabilities, it has build file available and it has low support. You can download it from GitHub.

k-nearest neighbors (KNN) classifier algorithm implementation in python.

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Quality

Security

License

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Support

knn-python has a low active ecosystem.

It has 1 star(s) with 0 fork(s). There are 2 watchers for this library.

It had no major release in the last 6 months.

knn-python has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of knn-python is current.

Quality

knn-python has no bugs reported.

Security

knn-python has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

knn-python 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.

Reuse

knn-python releases are not available. You will need to build from source code and install.

Build file is available. You can build the component from source.

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knn-python Key Features

No Key Features are available at this moment for knn-python.

knn-python Examples and Code Snippets

No Code Snippets are available at this moment for knn-python.

Community Discussions

No Community Discussions are available at this moment for knn-python.Refer to stack overflow page for discussions.

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

Vulnerabilities

No vulnerabilities reported

Install knn-python

You can download it from GitHub.
You can use knn-python 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 .

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