pyprimal 0.0.0

PYthon package PaRametric sImplex Method for spArse Learning

PYPRIMAL

PYPRIMAL: PYthon package PaRametric sImplex Method for spArse Learning

Requirements

• Linux or MacOS

Installation

Install from source file (Github) with Makefile:

• Clone primal.git via git clone --recurse-submodules https://github.com/ShenQianli/primal.git
• Make sure you have setuptools
• Run make Pyinstall command.

Install from source file (Github) with CMAKE:

• Clone primal.git via git clone --recurse-submodules https://github.com/ShenQianli/primal.git
• Make sure you have setuptools
• Build the source file first via the cmake with CMakeLists.txt in the root directory. (You will see a .so or .dylib file under (root)/lib/ )
• Run cd python-package; sudo python setup.py install command.

Install from PyPI:

• pip install pyprimal
• Note: Owing to the setting on different OS, our distribution might not be working in your environment (especially in Windows). Thus please build from source.

You can test if the package has been successfully installed by:

import pyprimal
pyprimal.test()

Usage

from pyprimal import SparseSVM
x = [[1,2,3], [4,5,6], [7,8,9]]
y = [-1, 1, 1]
solver = SparseSVM(x, y)
solver.train()
result = solver.coef()
solver.plot()
solver.plot('regpath')

See tutorial

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Author: Qianli Shen, Zichong Li
Maintainer: Qianli Shen [e-mail]