Skip to content

Navigation Menu

Sign in
Appearance settings

Search code, repositories, users, issues, pull requests...

Provide feedback

We read every piece of feedback, and take your input very seriously.

Saved searches

Use saved searches to filter your results more quickly

Sign up
Appearance settings

livetodeath0451/lwpr

Repository files navigation

Contents of the LWPR library 
(C) 2007 Stefan Klanke and Sethu Vijayakumar
sethu.vijayakumar@ed.ac.uk
The library is freely available under the terms of the LGPL 
with an exception that allows for static linking, see the
file COPYING.
Please see the file INSTALL.TXT for installation instructions.
Inside the top-level directory created after unzipping the archive, 
there are several subdirectories that contain sources, include files 
and documentation for programming languages other than Matlab:
doc
 contains supplementary documentation and hints how to tune 
 learning parameters etc. 
matlab
 contains the Matlab functions (.m files). To use the LWPR library 
 from Matlab, all you have to do is to add this directory to your 
 Matlab path, and to run "lwpr_buildmex" within Matlab in order to 
 build the MEX wrappers. Recent versions of Octave (2.9.12 or later) 
 are compatible with Matlab's MEX-interface, and thus the build 
 script we provide works in that environment as well. 
include
 C header files of the LWPR library. 
 C++ header (lwpr.hh) file for wrapping the C library as a C++ class
src
 C sources.
mexsrc / mexoct
 C sources of Matlab/Octave MEX-wrappers, as well as directives 
 for building them using GNU autotools. On Windows, building 
 the MEX files is handled by the script lwpr_buildmex, so 
 probably you will not have to look into these.
 
example_c
 contains a simple demo that shows how to use the library from 
 a C program. 
 
example_cpp
 contains a demo how to use the C++ wrapper to call the LWPR library 
 in C++ style. 
 
python
 contains a Python extension module for LWPR, written in C, and 
 also a Python script demonstrating its usage. If you have Python's 
 distutils installed, you can build the extension using setup.py, 
 otherwise try the included Makefile on a Linux/Unix system.
 Please note that you need to have "numpy" already installed on
 your system.
 
html
 contains documentation for the C and C++ modules as generated 
 by Doxygen.
 
VisualC
 Visual Studio "solutions" and project files. Only tested with
 Visual Studio Express 2008.
MingW
 Contains a simple Makefile for building the C library and
 examples on Windows using the MinGW compiler. Probably also
 works with Cygwin.
tests
 Contains a simple test program (written in C) that checks
 some aspects of the library during a "make check" call
 on UNIX-like systems.
THIS SOURCE CODE IS SUPPLIED "AS IS" WITHOUT WARRANTY OF ANY KIND, 
AND ITS AUTHOR AND THE JOURNAL OF MACHINE LEARNING RESEARCH (JMLR) 
AND JMLR'S PUBLISHERS AND DISTRIBUTORS, DISCLAIM ANY AND ALL 
WARRANTIES, INCLUDING BUT NOT LIMITED TO ANY IMPLIED WARRANTIES
OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE, AND 
ANY WARRANTIES OR NON INFRINGEMENT. THE USER ASSUMES ALL LIABILITY 
AND RESPONSIBILITY FOR USE OF THIS SOURCE CODE, AND NEITHER THE 
AUTHOR NOR JMLR, NOR JMLR'S PUBLISHERS AND DISTRIBUTORS, WILL BE 
LIABLE FOR DAMAGES OF ANY KIND RESULTING FROM ITS USE. 
Without limiting the generality of the foregoing, neither the 
author, nor JMLR, nor JMLR's publishers and distributors, warrant 
that the Source Code will be error-free, will operate without 
interruption, or will meet the needs of the user.

About

Locally Weighted Projection Regression

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

Contributors

Languages

  • C 56.9%
  • MATLAB 21.2%
  • C++ 18.3%
  • CMake 2.9%
  • Python 0.7%

AltStyle によって変換されたページ (->オリジナル) /