CHIC is a data analysis tool based on SIA. Its aim is to discover the more relevant implications between states of different variables. It proposes two different ways to organize these implications into systems: i) In the form of an oriented hierarchical tree and ii) as an implication graph. Besides, it also produces a (non oriented) similarity tree based on the likelihood of the links between states. The paper describes its main features and its usage.
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© 2008 Springer-Verlag Berlin Heidelberg
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Couturier, R. (2008). CHIC: Cohesive Hierarchical Implicative Classification. In: Gras, R., Suzuki, E., Guillet, F., Spagnolo, F. (eds) Statistical Implicative Analysis. Studies in Computational Intelligence, vol 127. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78983-3_2
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DOI: https://doi.org/10.1007/978-3-540-78983-3_2
Publisher Name: Springer, Berlin, Heidelberg
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