Change search
ReferencesLink to record
Permanent link

Direct link
Chipper: A Novel Algorithm for Concept Description
University of Borås, School of Business and IT.
University of Borås, School of Business and IT.
University of Borås, School of Business and IT.
2008 (English)Conference paper (Refereed)
Abstract [en]

In this paper, several demands placed on concept description algorithms are identified and discussed. The most important criterion is the ability to produce compact rule sets that, in a natural and accurate way, describe the most important relationships in the underlying domain. An algorithm based on the identified criteria is presented and evaluated. The algorithm, named Chipper, produces decision lists, where each rule covers a maximum number of remaining instances while meeting requested accuracy requirements. In the experiments, Chipper is evaluated on nine UCI data sets. The main result is that Chipper produces compact and understandable rule sets, clearly fulfilling the overall goal of concept description. In the experiments, Chipper's accuracy is similar to standard decision tree and rule induction algorithms, while rule sets have superior comprehensibility.

Place, publisher, year, edition, pages
IOS Press , 2008.
Keyword [en]
concept description, decision lists, nachine learning, Machine Learning, Data Mining, Computer Science
Keyword [sv]
data mining
National Category
Computer and Information Science Information Systems
URN: urn:nbn:se:hb:diva-6036Local ID: 2320/4352ISBN: 978-1-58603-867-0OAI: diva2:886720
Paper presented at the 10th Scandinavian Conference on Artificial Intelligence SCAI 2008
Available from: 2015-12-22 Created: 2015-12-22

Open Access in DiVA

fulltext(254 kB)11 downloads
File information
File name FULLTEXT01.pdfFile size 254 kBChecksum SHA-512
Type fulltextMimetype application/pdf

Search in DiVA

By author/editor
Johansson, UlfSönströd, CeciliaLöfström, Tuve
By organisation
School of Business and IT
Computer and Information ScienceInformation Systems

Search outside of DiVA

GoogleGoogle Scholar
Total: 11 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Total: 11 hits
ReferencesLink to record
Permanent link

Direct link