Project details for libcluster

Screenshot libcluster 2.3

by dsteinberg - February 27, 2016, 00:36:01 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ]

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Description:

This library implements the following algorithms and functions in C++ with python (2.7 and 3) and C++ interfaces:

  • The variational Dirichlet process (VDP)
  • The Bayesian Gaussian mixture model (BGMM)
  • Gaussian latent Dirichlet allocation (LDA with Gaussian observations)
  • Simultaneous Clustering Model (SCM) for Multinomial Documents, and Gaussian Observations
  • Multiple-source Clustering Model (MCM) for clustering two observations, one of an image/document, and multiple of segments/words simultaneously
  • And more clustering algorithms based on diagonal Gaussian, and Exponential distributions
  • It is a template-based library, and so new algorithms can be defined by creating new distribution objects
  • Various functions for evaluating means, standard deviations, covariance, primary Eigenvalues etc of data
Changes to previous version:

New maximum cluster argument for all algorithms. Also no more matlab interface since it seemed no one was using it, and I cannot support it any longer.

BibTeX Entry: Download
Corresponding Paper BibTeX Entry: Download
URL: Project Homepage
Supported Operating Systems: Linux, Mac
Data Formats: Numpy, Any Format Supported By Matlab, Eigen Matrix
Tags: Clustering, Gmm, Density Estimation, Approximate Inference, Mean Field, Gaussian Mixture Models, Latent Dirichlet Allocation, Hierarchical Models, Bayesian, Latent Variable Model, Mixture Model, Multi
Archive: download here

Other available revisons

Version Changelog Date
2.3

New maximum cluster argument for all algorithms. Also no more matlab interface since it seemed no one was using it, and I cannot support it any longer.

February 27, 2016, 00:36:01
2.2

Python 2 & 3 interface fixes and minor updates. Now uses Travis-CI as well.

January 24, 2016, 03:32:49
2.1

Initial Announcement on mloss.org.

October 31, 2014, 23:27:57

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