pyGP | Gaussian Processes in python | Analytics library

by jameshensman Python Version: Current License: GPL-3.0

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | pyGP Summary

pyGP is a Python library typically used in Analytics applications. pyGP has no bugs, it has no vulnerabilities, it has a Strong Copyleft License and it has low support. However pyGP build file is not available. You can download it from GitHub.

Gaussian processes and related models in python. Copyright James Hensman and Michael Dewar 2009.

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Quality

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License

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Support

pyGP has a low active ecosystem.

It has 8 star(s) with 0 fork(s). There are 3 watchers for this library.

It had no major release in the last 6 months.

There are 1 open issues and 1 have been closed. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of pyGP is current.

Quality

pyGP has no bugs reported.

Security

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

License

pyGP is licensed under the GPL-3.0 License. This license is Strong Copyleft.

Strong Copyleft licenses enforce sharing, and you can use them when creating open source projects.

Reuse

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

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

Finds the kernel parameters
Log likelihood of the hyperparameters
Update the covariance matrix
Hyperparameter prior
Marginal marginal distribution
Set the parameters
Return the model parameters
Calculate the gradient of the gradient of the likelihood
Update the gradients of the covariance matrix
The hyperprior gradient of hyperparameters
Log likelihood
Unpack weights
Compute the output function
Calculate the gradient of the forward gradient
Backward propagation
Forward computation
Calculate the error

Get all kandi verified functions for this library.

pyGP Key Features

No Key Features are available at this moment for pyGP.

pyGP Examples and Code Snippets

No Code Snippets are available at this moment for pyGP.

Community Discussions

Trending Discussions on pyGP

Wrapping C++ class in Python with SWIG

QUESTION

Wrapping C++ class in Python with SWIG

Asked 2017-May-14 at 21:23

I have the following C++ class that I wish to wrap in Python with SWIG.

...

ANSWER

Answered 2017-May-14 at 12:41

If look into the examples in the numpy.i header, you will see examples of how to apply the NumPy typemaps.

In your case, you should change

Source https://stackoverflow.com/questions/43954870

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

Vulnerabilities

No vulnerabilities reported

Install pyGP

You can download it from GitHub.
You can use pyGP 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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