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Algorithm::KMeans is a perl5 module for the clustering of numerical data

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in multidimensional spaces. Since the module is entirely in Perl (in the
sense that it is not a Perl wrapper around a C library that actually does
the clustering), the code in the module can easily be modified to experiment
with several aspects of automatic clustering. For example, one can change
the criterion used to measure the "distance" between two data points, the
stopping condition for accepting final clusters, the criterion used for
measuring the quality of the clustering achieved, etc.

WWW: http://search.cpan.org/dist/Algorithm-KMeans

Feature safe:	yes
This commit is contained in:
Wen Heping 2010-07-01 04:16:41 +00:00
parent ea7a9a82fe
commit e1daee4b97
Notes: svn2git 2021-03-31 03:12:20 +00:00 
svn path=/head/; revision=257239
5 changed files with 41 additions and 0 deletions
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1
math/Makefile
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@ -292,6 +292,7 @@
SUBDIR += p5-AI-Perceptron
SUBDIR += p5-Algorithm-Combinatorics
SUBDIR += p5-Algorithm-CurveFit
SUBDIR += p5-Algorithm-KMeans
SUBDIR += p5-Algorithm-Munkres
SUBDIR += p5-Bit-ShiftReg
SUBDIR += p5-Bit-Vector

21
math/p5-Algorithm-KMeans/Makefile Normal file
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@ -0,0 +1,21 @@
# New ports collection makefile for: p5-Algorithm-KMeans
# Date created: 30 June, 2010
# Whom: Wen Heping <wen@FreeBSD.org>
#
# $FreeBSD$
#
PORTNAME= Algorithm-KMeans
PORTVERSION= 1.1.1
CATEGORIES= math perl5
MASTER_SITES= CPAN/../../authors/id/A/AV/AVIKAK/
PKGNAMEPREFIX= p5-
MAINTAINER= wen@FreeBSD.org
COMMENT= Clustering multi-dimensional data with a pure-Perl implementation
MAN3= Algorithm::KMeans.3
PERL_CONFIGURE= yes
.include <bsd.port.mk>

3
math/p5-Algorithm-KMeans/distinfo Normal file
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@ -0,0 +1,3 @@
MD5 (Algorithm-KMeans-1.1.1.tar.gz) = f56cf7cee1f78614bc0947854af5e106
SHA256 (Algorithm-KMeans-1.1.1.tar.gz) = 90189133f9760f0f6cbe311830b0db930a5d8259e87de48c86631caf61f79ec1
SIZE (Algorithm-KMeans-1.1.1.tar.gz) = 26494

10
math/p5-Algorithm-KMeans/pkg-descr Normal file
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@ -0,0 +1,10 @@
Algorithm::KMeans is a perl5 module for the clustering of numerical data
in multidimensional spaces. Since the module is entirely in Perl (in the
sense that it is not a Perl wrapper around a C library that actually does
the clustering), the code in the module can easily be modified to experiment
with several aspects of automatic clustering. For example, one can change
the criterion used to measure the "distance" between two data points, the
stopping condition for accepting final clusters, the criterion used for
measuring the quality of the clustering achieved, etc.
WWW: http://search.cpan.org/dist/Algorithm-KMeans

6
math/p5-Algorithm-KMeans/pkg-plist Normal file
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@ -0,0 +1,6 @@
%%SITE_PERL%%/Algorithm/KMeans.pm
%%SITE_PERL%%/%%PERL_ARCH%%/auto/Algorithm/KMeans/.packlist
@dirrm %%SITE_PERL%%/%%PERL_ARCH%%/auto/Algorithm/KMeans
@dirrmtry %%SITE_PERL%%/%%PERL_ARCH%%/auto/Algorithm
@dirrm %%SITE_PERL%%/Algorithm/KMeans
@dirrmtry %%SITE_PERL%%/Algorithm