.. -- mode: rst --
|Travis|_ |PyPi|_
.. |Travis| image:: https://travis-ci.com/ocampor/libsvm.svg?branch=master .. _Travis: https://travis-ci.com/ocampor/libsvm
.. |PyPi| image:: https://img.shields.io/pypi/dm/libsvm?color=blue :alt: PyPI - Downloads .. _PyPi: https://pypi.org/project/libsvm/
Pre-built LibSVM packages for Python.
Crated by Chih-Chung Chang and Chih-Jen Lin, LIBSVM is an integrated software for support vector classification, (C-SVC, nu-SVC), regression (epsilon-SVR, nu-SVR) and distribution estimation (one-class SVM). It supports multi-class classification.
The idea behind this package is to use the same code as in https://github.com/cjlin1/libsvm using the very convenient pip command
::
pip install libsvm
::
from libsvm.svmutil import * y, x = svm_read_problem('path/to/heart_scale') m = svm_train(y[:200], x[:200], '-c 4') . optimization finished, #iter = 257 nu = 0.351161 obj = -225.628984, rho = 0.636110 nSV = 91, nBSV = 49 Total nSV = 91 p_label, p_acc, p_val = svm_predict(y[200:], x[200:], m) Accuracy = 84.2857% (59/70) (classification)
The package contains a pre-built Windows binary that is only compatible with 64 bits architecture; therefore, 32 bits architecture is not compatible.
Cygwin
In case that you want to install this package using Cygwin, you have to make sure that the following packages are installed:
Some good tutorials to install Cygwin packages are the following:
Copyright (c) 2000-2018 Chih-Chung Chang and Chih-Jen Lin All rights reserved.
Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:
Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
Neither name of copyright holders nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE REGENTS OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
me@ocampor.ai_FAQs
Pre-built LibSVM packages for Python.
We found that libsvm demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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