This software provides a Perl interface to the C Clustering Library, allowing users to easily perform clustering analysis in Perl-based programs.
The Algorithm::Cluster is a Perl interface to the C Clustering Library which is a general-purpose library implementing functions for hierarchical clustering. It offers pairwise simple, complete, average and centroid linkage, along with k-means and k-medians clustering and 2D self-organizing maps.
The library was developed at the Human Genome Center of the University of Tokyo and is distributed along with Cluster 3.0, which is an enhanced version of the famous Cluster program developed by Michael Eisen while at Stanford University.
The Algorithm::Cluster module provides users with a simple and efficient means of accessing the C Clustering Library. It can be used for a wide range of applications including data visualization and analysis. By leveraging the clustering algorithms included in this module, users can easily group similar data points and quickly identify patterns and trends.
Overall, Algorithm::Cluster is a powerful tool for anyone looking to perform clustering analysis and visualization in Perl. With its intuitive interface and broad set of features, this module is a must-have for any serious data scientist or researcher.
The library was developed at the Human Genome Center of the University of Tokyo and is distributed along with Cluster 3.0, which is an enhanced version of the famous Cluster program developed by Michael Eisen while at Stanford University.
The Algorithm::Cluster module provides users with a simple and efficient means of accessing the C Clustering Library. It can be used for a wide range of applications including data visualization and analysis. By leveraging the clustering algorithms included in this module, users can easily group similar data points and quickly identify patterns and trends.
Overall, Algorithm::Cluster is a powerful tool for anyone looking to perform clustering analysis and visualization in Perl. With its intuitive interface and broad set of features, this module is a must-have for any serious data scientist or researcher.
What's New
Version 1.46: N/A