Post-processing: bridging the gap between modelling and effective decision-support. The Profile Assessment Grid in Human Behaviour
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Tipus de documentArticle
Data publicació2011-11-28
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Abstract
The importance of post-processing the results of clustering when using data mining to
support subsequent decision-making is discussed. Both the formal embedded binary logistic
regression (EBLR) and the visual profile’s assessment grid (PAG) methods are presented
as bridging tools for the real use of clustering results. EBLR is a sequence of logistic
regressions that helps to predict the class of a new object; while PAG is a graphical tool that
visualises the results of an EBLR. PAG interactively determines the most suitable class for a
new object and enables subsequent follow-ups. PAG makes the underlying mathematical
model (EBLR) more understandable, improves usability and contributes to bridging the gap
between modelling and decision-support. When applied to medical problems, these tools
can perform as diagnostic-support tools, provided that the predefined set of profiles refer
to different stages of a certain disease or different types of patients with a same medical
problem, etc. Being a graphical tool, PAG enables doctors to quickly and friendly determine
the profile of a patient in the everyday activity, without necessarily understanding the
statistical models involved in the process, which used to be a serious limitation for wider
application of these methods in clinical praxis. In this work, an application is presented
with 4 functional disability profiles.
CitacióGibert, Karina; Rodríguez, G.; Annicchiarico, R. Post-processing: bridging the gap between modelling and effective decision-support. The Profile Assessment Grid in Human Behaviour. "Mathematical and computer modeling", 28 Novembre 2011, vol. 57, núm. 7-8, p. 1633-1639.
ISSN0895-7177
Versió de l'editorhttp://upcommons.upc.edu/e-prints/urlFiles?idDrac=8756896
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