Introduction¶
NonlinearRegression is a small suit of tools to perform nonlinear regression, scikitlearn style.
It uses linear regression and data transformation to perform unweighted nonlinear regression
and implements a version of function spaces as Hilbert spaces to do weighted nonlinear regression.
Also, has a simple class to cross validate time series when treated as a regression problem.
Dependencies¶
Download¶
NonlinearRegression can be obtained from https://gitlab.com/mghasemi/nonlinear-regression.
Installation¶
To install NonlinearRegression, run the following in terminal:
sudo python setup.py install
Documentation¶
The documentation is produced by Sphinx and is intended to cover code usage as well as a bit of theory to explain each method briefly. For more details refer to the documentation at sksurrogate.rtfd.io.
License¶
This code is distributed under MIT license:
MIT License¶
Copyright (c) 2020 Mehdi Ghasemi
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.