A tool for interactive subgroup discovery using distribution rules

• Type: Chapter or Part of a Book
• Date: 2007

Authors

Joel P Lucas (Author) Other; Alipio M Jorge (Author) FEP; Fernando Pereira (Author) Other; Ana M PernaS (Author) Other; Amauri A Machado (Author) Other

Book

Title: Progress in Artificial Intelligence

Pages: 426-436

Indexing

ISI Web of Knowledge - 3 Citations

Scopus - 4 Citations

Scientific classification

FOS: Natural sciences > Computer and information sciences

Other information

Authenticus ID: P-004-EFH

DOI: 10.1007/978-3-540-77002-2_36

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.

Language: English

Type (Professor's evaluation): Scientific

Notes: Part of the Lecture Notes in Computer Science book series (LNCS, volume 4874) Print ISBN: 978-3-540-77000-8

No. of pages: 11