Project details for Dependency modeling toolbox

Screenshot Dependency modeling toolbox 0.2

by lml - April 30, 2010, 14:38:45 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ]

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Investigation of dependencies between multiple data sources allows the discovery of regularities and interactions that are not seen in individual data sets. The increasing availability of co-occurring measurement data in computational biology, social sciences, and in other domains emphasizes the need for practical implementations of general-purpose dependency modeling algorithms.

The project collects various dependency modeling approaches into a unified toolbox. The techniques for the discovery and analysis of statistical dependencies are based on well-established models such as probabilistic canonical correlation analysis and multi-task learning whose applicability has been demonstrated in previous case studies.

Changes to previous version:

Three independent modules (drCCA, pint, MultiWayCCA) have been added.

BibTeX Entry: Download
Corresponding Paper BibTeX Entry: Download
Supported Operating Systems: Platform Independent
Data Formats: Agnostic
Tags: Bioinformatics, Machine Learning, Statistics, Learning Principles, Probabilistic Models, Icml2010
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Other available revisons

Version Changelog Date

Three independent modules (drCCA, pint, MultiWayCCA) have been added.

April 30, 2010, 09:46:52

Initial Announcement on

April 8, 2010, 16:47:04


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