Algorithms for Learning Decomposable Models and Chordal Graphs

📝 Original Info

• Title: Algorithms for Learning Decomposable Models and Chordal Graphs
• ArXiv ID: 1302.1524
• Date: 2013-02-08
• Authors: Researchers from original ArXiv paper

📝 Abstract

Decomposable dependency models and their graphical counterparts, i.e., chordal graphs, possess a number of interesting and useful properties. On the basis of two characterizations of decomposable models in terms of independence relationships, we develop an exact algorithm for recovering the chordal graphical representation of any given decomposable model. We also propose an algorithm for learning chordal approximations of dependency models isomorphic to general undirected graphs.

💡 Deep Analysis

Deep Dive into Algorithms for Learning Decomposable Models and Chordal Graphs.

Decomposable dependency models and their graphical counterparts, i.e., chordal graphs, possess a number of interesting and useful properties. On the basis of two characterizations of decomposable models in terms of independence relationships, we develop an exact algorithm for recovering the chordal graphical representation of any given decomposable model. We also propose an algorithm for learning chordal approximations of dependency models isomorphic to general undirected graphs.

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