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Vowpal Wabbit recipe (does not include Python or R wrappers yet)
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#! /bin/sh | |
export BOOST_ROOT="${PREFIX}/include/boost" | |
export LDFLAGS="-L${PREFIX}/lib" | |
export CPPFLAGS="-I${PREFIX}/include" | |
./autogen.sh --prefix="${PREFIX}" --with-boost-libdir="${PREFIX}/lib" | |
make -j${CPU_COUNT} | |
make install |
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Copyright © Microsoft Corp 2012-2014, Yahoo! Inc. 2007-2012, and many | |
individual contributors. | |
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 the name of the Microsoft Corp 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 <COPYRIGHT HOLDER> 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. |
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{% set name = "vowpal-wabbit" %} | |
{% set version = "8.6.1" %} | |
package: | |
name: {{ name|lower }} | |
version: {{ version }} | |
source: | |
url: https://github.com/VowpalWabbit/vowpal_wabbit/archive/{{ version }}.tar.gz | |
sha256: 452c3e83b73fd67f5e9cfae8bfbaf398cda73dc688186b376e6106c376ec5eb1 | |
#git_url: https://github.com/VowpalWabbit/vowpal_wabbit | |
#git_tag: {{ version }} | |
build: | |
number: 0 | |
#run_exports: | |
# - zlib | |
# - boost | |
requirements: | |
build: | |
#- {{ compiler('c') }} | |
#- {{ compiler('cxx') }} | |
- gxx_linux-64 | |
- libstdcxx-ng | |
- binutils_linux-64 | |
- make | |
host: | |
- zlib | |
- boost | |
run: | |
- zlib | |
- boost | |
test: | |
commands: | |
- vw --version | |
- vw --help | |
about: | |
home: http://hunch.net/~vw/ | |
license_file: {{ RECIPE_DIR }}/LICENSE | |
summary: | | |
Vowpal Wabbit is a machine learning system which pushes the frontier of | |
machine learning with techniques such as online, hashing, allreduce, | |
reductions, learning2search, active, and interactive learning. | |
description: | | |
This is a project started at Yahoo! Research and continuing at Microsoft | |
Research to design a fast, scalable, useful learning algorithm. VW is the | |
essence of speed in machine learning, able to learn from terafeature | |
datasets with ease. Via parallel learning, it can exceed the throughput of | |
any single machine network interface when doing linear learning, a first | |
amongst learning algorithms. | |
doc_url: https://github.com/VowpalWabbit/vowpal_wabbit/wiki | |
dev_url: https://github.com/VowpalWabbit/vowpal_wabbit | |
extra: | |
recipe-maintainers: | |
- gwerbin |
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