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- science/liblr is moved to science/liblinear (project renamed)

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This commit is contained in:
Rong-En Fan 2007-07-28 07:10:54 +00:00
parent a649a6476d
commit 6229775fac
Notes: svn2git 2021-03-31 03:12:20 +00:00 
svn path=/head/; revision=196441
5 changed files with 2 additions and 70 deletions
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1
MOVED
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@ -3108,3 +3108,4 @@ french/fr-py-qt4-eric4|french/eric4|2007-07-25|Moved to french/eric4
german/de-py-qt4-eric4|german/eric4|2007-07-25|Moved to german/eric4
russian/ru-py-qt4-eric4|russian/eric4|2007-07-25|Moved to russian/eric4
devel/py-qt4-eric4|devel/eric4|2007-07-25|Moved to devel/eric4
science/liblr|science/liblinear|2007-07-28|Project renamed

2
science/Makefile
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@ -66,7 +66,7 @@
SUBDIR += libctl
SUBDIR += libghemical
SUBDIR += libint
SUBDIR += liblr
SUBDIR += liblinear
SUBDIR += libsvm
SUBDIR += libsvm-python
SUBDIR += linsmith

50
science/liblr/Makefile
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@ -1,50 +0,0 @@
# New ports collection Makefile for: liblr
# Date created: May 14 2007
# Whom: Rong-En Fan <rafan@FreeBSD.org>
#
# $FreeBSD$
#
PORTNAME= liblr
PORTVERSION= 1.00
CATEGORIES= science math
MASTER_SITES= http://www.csie.ntu.edu.tw/~cjlin/liblinear/oldfiles/
DISTNAME= ${PORTNAME}-${PORTVERSION:C/0$//}
MAINTAINER= rafan@FreeBSD.org
COMMENT= A library for Large Regularized Logistic Regression
OPTIONS= OCFLAGS "Use optimized CFLAGS" On
USE_ZIP= yes
MAKE_ENV= CC="${CC}" CXXC="${CXX}"
TXT_DOCS= COPYRIGHT README
.if !defined(NOPORTDOCS)
PORTDOCS= ${TXT_DOCS}
.endif
PLIST_FILES= bin/lr-train bin/lr-predict
.include <bsd.port.pre.mk>
.if !defined(WITHOUT_OCFLAGS)
# same as LIBIR itself
CFLAGS= -Wall -O3
.endif
do-install:
${INSTALL_PROGRAM} ${WRKSRC}/lr-train ${TARGETDIR}/bin/
${INSTALL_PROGRAM} ${WRKSRC}/lr-predict ${TARGETDIR}/bin/
post-install:
.if !defined(NOPORTDOCS)
@${MKDIR} ${DOCSDIR}
for f in ${TXT_DOCS}; do \
${INSTALL_DATA} ${WRKSRC}/$$f ${DOCSDIR}; \
done
.endif
.include <bsd.port.post.mk>

3
science/liblr/distinfo
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@ -1,3 +0,0 @@
MD5 (liblr-1.0.zip) = 6407b44f889c1465df341d5242f30480
SHA256 (liblr-1.0.zip) = 1435e9dd96f9723872dc624d0ea3a12b0b6ab5d7240f41765c3fd69677bcbed3
SIZE (liblr-1.0.zip) = 153199

16
science/liblr/pkg-descr
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@ -1,16 +0,0 @@
LIBLR is a linear classifier for data with millions of instances and
features. It implement a trust region Newton method in
C.-J. Lin, R. C. Weng, and S. S. Keerthi. Trust region Newton method
for large-scale regularized logistic regression. Technical report, 2007.
A short version appears in ICML 2007.
Main features of LIBLR include
Same data format as LIBSVM and similar usage
One-vs-the rest multi-class classification
Cross validation for model selection
Probability estimates
Weights for unbalanced data
WWW: http://www.csie.ntu.edu.tw/~cjlin/liblr/