Search results for "module:Algorithm::Cluster"

Algorithm::Cluster - Perl interface to the C Clustering Library. River stage one • 2 direct dependents • 2 total dependents

This module is an interface to the C Clustering Library, a general purpose library implementing functions for hierarchical clustering (pairwise simple, complete, average, and centroid linkage), along with k-means and k-medians clustering, and 2D self...

MDEHOON/Algorithm-Cluster-1.59 - 30 Aug 2019 12:39:17 UTC

Algorithm::Cluster::Thresh - Adds thresholding to hierarchical clustering of Algorithm::Cluster River stage zero No dependents

This is a small helper package for Algorithm::Cluster, but not an official part of it. That manual can be found here: http://cpansearch.perl.org/src/MDEHOON/Algorithm-Cluster-1.48/doc/cluster.pdf This package adds a simple method "$tree-"cutthresh(5....

CADAVIS/Algorithm-Cluster-Thresh-0.05 - 29 Jun 2011 09:00:10 UTC

Text::Mining::Algorithm::Cluster - Perl Tools for Text Mining River stage zero No dependents

ROGERHALL/Text-Mining-0.08 - 15 Mar 2009 17:06:03 UTC

perl/Record.pm River stage one • 2 direct dependents • 2 total dependents

MDEHOON/Algorithm-Cluster-1.59 - 30 Aug 2019 12:39:17 UTC

Algorithm::ClusterPoints - find clusters inside a set of points River stage zero No dependents

This module implements an algorithm to find clusters of points inside a set. Clusters are defined as sets of points where it is possible to stablish a way between any pair of points moving from point to point inside the cluster in steps smaller than ...

SALVA/Algorithm-ClusterPoints-0.08 - 10 Jul 2008 13:24:27 UTC

Algorithm::MCL - perl module implementing Markov Cluster Algorithm using PDL River stage zero No dependents

This module is perl implementation of Markov Cluster Algorithm (MCL) based on Perl Data Language (PDL). MCL is algorithm of finding clusters of vertices in graph. More information about MCL can be found at <http://micans.org/mcl/>. There is also perl...

PINKHASN/Algorithm-MCL-0.004 - 03 Mar 2012 20:55:45 UTC

Algorithm::KMeans - for clustering multidimensional data River stage zero No dependents

Clustering with K-Means takes place iteratively and involves two steps: 1) assignment of data samples to clusters on the basis of how far the data samples are from the cluster centers; and 2) Recalculation of the cluster centers (and cluster covarian...

AVIKAK/Algorithm-KMeans-2.05 - 12 Dec 2014 01:48:47 UTC

Algorithm::DBSCAN - (ALFA code) Perl implementation of the DBSCAN (Density-Based Spatial Clustering of Applications with Noise) algorithm River stage zero No dependents

MTOMA/Algorithm-DBSCAN-0.07 - 05 Mar 2016 06:29:40 UTC

Algorithm::Kmeanspp - perl implementation of K-means++ River stage zero No dependents

Algorithm::Kmeanspp is a perl implementation of K-means++....

FUJISAWA/Algorithm-Kmeanspp-0.03 - 16 Oct 2009 02:55:01 UTC

Algorithm::FuzzyCmeans - perl implementation of Fuzzy c-means clustering River stage zero No dependents

Algorithm::FuzzyCmeans is a perl implementation of Fuzzy c-means clustering....

FUJISAWA/Algorithm-FuzzyCmeans-0.02 - 16 Oct 2009 02:54:50 UTC

Algorithm::KernelKMeans - Weighted kernel k-means clusterer River stage zero No dependents

"Algorithm::KernelKMeans" provides weighted kernel k-means vector clusterer. Note that this is a very early release. All APIs may be changed incompatibly. IMPLEMENTATION This class is just a placeholder. Implementation code is in other class and this...

SEKIA/Algorithm-KernelKMeans-0.03 - 10 Nov 2010 15:16:15 UTC

Algorithm::DistanceMatrix - Compute distance matrix for any distance metric River stage zero No dependents

This is a small helper package for Algorithm::Cluster. That module provides many facilities for clustering data. It also provides a "distancematrix" function, but assumes tabular data, which is the standard for gene expression data. If your data is t...

CADAVIS/Algorithm-DistanceMatrix-0.04 - 27 Jun 2011 07:40:26 UTC

Algorithm::KernelKMeans::Util River stage zero No dependents

This module provides some utility functions suitable to use with "Algorithm::KernelKMeans"....

SEKIA/Algorithm-KernelKMeans-0.03 - 10 Nov 2010 15:16:15 UTC

Algorithm::Paxos::Role::Learner - A Learner role for the Paxos algorithm River stage zero No dependents

From Wikipedia <http://en.wikipedia.org/wiki/Paxos_algorithm> Learners act as the replication factor for the protocol. Once a Client request has been agreed on by the Acceptors, the Learner may take action (i.e.: execute the request and send a respon...

PERIGRIN/Algorithm-Paxos-0.001 - 03 Jan 2012 19:20:37 UTC

Algorithm::Paxos::Role::Proposer - A Proposer role for the Paxos algorithm River stage zero No dependents

From Wikipedia <http://en.wikipedia.org/wiki/Paxos_algorithm> A Proposer advocates a client request, attempting to convince the Acceptors to agree on it, and acting as a coordinator to move the protocol forward when conflicts occur....

PERIGRIN/Algorithm-Paxos-0.001 - 03 Jan 2012 19:20:37 UTC

Algorithm::ExpectationMaximization - A Perl module for clustering numerical multi-dimensional data with the Expectation-Maximization algorithm. River stage zero No dependents

Algorithm::ExpectationMaximization is a *perl5* module for the Expectation-Maximization (EM) method of clustering numerical data that lends itself to modeling as a Gaussian mixture. Since the module is entirely in Perl (in the sense that it is not a ...

AVIKAK/Algorithm-ExpectationMaximization-1.22 - 11 Dec 2014 15:38:37 UTC

Algorithm::LinearManifoldDataClusterer - for clustering data that resides on a low-dimensional manifold in a high-dimensional measurement space River stage zero No dependents

If you are new to machine learning and data clustering on linear and nonlinear manifolds, your first question is likely to be: What is a manifold? A manifold is a space that is locally Euclidean. And a space is locally Euclidean if it allows for the ...

AVIKAK/Algorithm-LinearManifoldDataClusterer-1.01 - 09 Jan 2015 18:39:55 UTC
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