svmpy | Basic soft-margin kernel SVM implementation in Python

by ajtulloch Python Version: 0.3 License: No License

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

kandi X-RAY | svmpy Summary

svmpy is a Python library. svmpy has no bugs, it has no vulnerabilities, it has build file available and it has low support. You can install using 'pip install svmpy' or download it from GitHub, PyPI.

Basic soft-margin kernel SVM implementation in Python

Support

Quality

Security

License

Reuse

Support

svmpy has a low active ecosystem.

It has 205 star(s) with 106 fork(s). There are 7 watchers for this library.

It had no major release in the last 12 months.

There are 4 open issues and 0 have been closed. On average issues are closed in 594 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of svmpy is 0.3

Quality

svmpy has 0 bugs and 6 code smells.

Security

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

svmpy code analysis shows 0 unresolved vulnerabilities.

There are 1 security hotspots that need review.

License

svmpy 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

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

Deployable package is available in PyPI.

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

svmpy saves you 46 person hours of effort in developing the same functionality from scratch.

It has 122 lines of code, 14 functions and 4 files.

It has low code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed svmpy and discovered the below as its top functions. This is intended to give you an instant insight into svmpy implemented functionality, and help decide if they suit your requirements.

Train the model
Compute multipliers
Constructs a prediction for the model
Predict value for given input data
Compute the kernel matrix
Constructs an inhomogenous polynomials
Construct a function that returns a polynomial
Return a homogenous polynomial

Get all kandi verified functions for this library.

svmpy Key Features

No Key Features are available at this moment for svmpy.

svmpy Examples and Code Snippets

No Code Snippets are available at this moment for svmpy.

Community Discussions

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

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

Vulnerabilities

No vulnerabilities reported

Install svmpy

You can install using 'pip install svmpy' or download it from GitHub, PyPI.
You can use svmpy 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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