libsvm 3.23.0

Description

Pre-built LibSVM packages for Python.

What is LibSVM?

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.

Original Links

• Repository: https://github.com/cjlin1/libsvm

• Library website: https://www.csie.ntu.edu.tw/~cjlin/libsvm

Purpose of this package

The idea behind this package is to use the same code as in https://github.com/cjlin1/libsvm using the very convenient pip command

How to install

pip install libsvm

Example

1. Download https://github.com/cjlin1/libsvm/blob/master/heart_scale file.

2. Run the following commands

>>> 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)

Copyright

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:

1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.

2. 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.

3. 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.

Maintainer

• Ricardo Ocampo me@ocampor.ai