Package: flexclust
Version: 1.1-1
Date: 2009-02-19
Author: Friedrich Leisch
Maintainer: Friedrich Leisch <Friedrich.Leisch@R-project.org>
Title: Flexible Cluster Algorithms
Depends: graphics, grid, lattice, modeltools (>= 0.2-16)
Imports: methods, stats, stats4
Suggests: ellipse, clue, cluster, seriation
Description: The main function kcca implements a general framework for
k-centroids cluster analysis supporting arbitrary distance measures
and centroid computation. Further cluster methods include hard
competitive learning, neural gas, and QT clustering. There are
numerous visualization methods for cluster results (neighborhood
graphs, convex cluster hulls, barcharts of centroids, ...), and
bootstrap methods for the analysis of cluster stability.
License: GPL-2
LazyLoad: yes
Packaged: Thu Feb 19 15:59:15 2009; leisch

Package: flexclust
Version: 1.1-2
Date: 2009-02-23
Author: Friedrich Leisch
Maintainer: Friedrich Leisch <Friedrich.Leisch@R-project.org>
Title: Flexible Cluster Algorithms
Depends: graphics, grid, lattice, modeltools (>= 0.2-16)
Imports: methods, stats, stats4
Suggests: ellipse, clue, cluster, seriation
Description: The main function kcca implements a general framework for
k-centroids cluster analysis supporting arbitrary distance measures
and centroid computation. Further cluster methods include hard
competitive learning, neural gas, and QT clustering. There are
numerous visualization methods for cluster results (neighborhood
graphs, convex cluster hulls, barcharts of centroids, ...), and
bootstrap methods for the analysis of cluster stability.
License: GPL-2
LazyLoad: yes
ZipData: no
Packaged: Mon Feb 23 11:32:49 2009; leisch

Suggests: ellipse, clue, cluster, seriation, multicore
k-centroids cluster analysis supporting arbitrary distance
measures and centroid computation. Further cluster methods
include hard competitive learning, neural gas, and QT
clustering. There are numerous visualization methods for
cluster results (neighborhood graphs, convex cluster hulls,
barcharts of centroids, ...), and bootstrap methods for the