## Graphical Explanation in Belief Networks (1997)

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Venue: | In Journal of Computational and Graphical Statistics |

Citations: | 15 - 4 self |

### BibTeX

@ARTICLE{Madigan97graphicalexplanation,

author = {David Madigan and Krzysztof Mosurski and Russell G Almond},

title = {Graphical Explanation in Belief Networks},

journal = {In Journal of Computational and Graphical Statistics},

year = {1997},

volume = {6},

pages = {160--181}

}

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### Abstract

Belief networks provide an important bridge between statistical modeling and expert systems. In this paper we present methods for visualizing probabilistic "evidence flows" in belief networks, thereby enabling belief networks to explain their behavior. Building on earlier research on explanation in expert systems, we present a hierarchy of explanations, ranging from simple colorings to detailed displays. Our approach complements parallel work on textual explanations in belief networks. GRAPHICAL-BELIEF, Mathsoft Inc.'s belief network software, implements the methods. 1 Introduction A fundamental reason for building a mathematical or statistical model is to foster deeper understanding of complex, real-world systems. Consequently, explanations---descriptions of the mechanisms which comprise such models---form an important part of model validation, exploration, and use. Early tests of rule-based expert system models indicated the critical need for detailed explanations in that setting (...