sklearn_pmml | Works for linear regression

by jeenalee Python Version: Current License: MIT

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

kandi X-RAY | sklearn_pmml Summary

sklearn_pmml is a Python library. sklearn_pmml has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub.

This is a library for converting PMML represented machine learning model into a scikit-learn classifier that can be used for prediction.

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Quality

Security

License

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Support

sklearn_pmml has a low active ecosystem.

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

It had no major release in the last 6 months.

sklearn_pmml has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of sklearn_pmml is current.

Quality

sklearn_pmml has no bugs reported.

Security

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

License

sklearn_pmml is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

sklearn_pmml 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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sklearn_pmml Key Features

No Key Features are available at this moment for sklearn_pmml.

sklearn_pmml Examples and Code Snippets

No Code Snippets are available at this moment for sklearn_pmml.

Community Discussions

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

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

Vulnerabilities

No vulnerabilities reported

Install sklearn_pmml

You can download it from GitHub.
You can use sklearn_pmml 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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