Abstract (EN):
We describe an approach and a tool for the discovery of subgroups within the framework of distribution rule mining. Distribution rules are a kind of association rules particularly suited for the exploratory study of numerical variables of interest. Being an exploratory technique, the result of a distribution mining process is typically a very large number of patterns. Exploring such results is thus a complex task and limits the use of the technique. To overcome this shortcoming we developed a tool, written in Java, which supports subgroup discovery in a post-processing step. The tool engages the analyst in an interactive process of subgroup discovery by means of a graphical interface with well defined statistical grounds, where domain knowledge can be used during the identification of such subgroups amid the population. We show a case study to analyze the results of students in a large scale university admission examination.
Idioma:
Inglês
Tipo (Avaliação Docente):
Científica
Notas:
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4874)
Print ISBN: 978-3-540-77000-8
Nº de páginas:
11