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Attribute ranking driven filtering of decision rules

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Citations (Scopus)

Abstract

In decision rule induction approaches either minimal, complete, or satisfying sets of constituent rules are inferred, with an aim of providing predictive properties while offering descriptive capabilities for the learned concepts. Instead of limiting rules at their induction phase we can also execute post-processing of the set of generated decision rules (whether it is complete or not) by filtering out those that meet some constraints. The paper presents the research on rule filtering while following a ranking of conditional attributes, obtained in the process of sequential forward selection of input features for ANN classifiers.

Original languageEnglish
Title of host publicationRough Sets and Intelligent Systems Paradigms - Second International Conference, RSEISP 2014, Held as Part of JRS 2014, Proceedings
PublisherSpringer Verlag
Pages217-224
Number of pages8
ISBN (Print)9783319087283
DOIs
Publication statusPublished - 2014
Event2nd International Conference on Rough Sets and Emerging Intelligent Systems Paradigms, RSEISP 2014 - Held as Part of 2014 Joint Rough Set Symposium, JRS 2014 - Granada and Madrid, Spain
Duration: 9 Jul 201413 Jul 2014

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8537 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference2nd International Conference on Rough Sets and Emerging Intelligent Systems Paradigms, RSEISP 2014 - Held as Part of 2014 Joint Rough Set Symposium, JRS 2014
Country/TerritorySpain
CityGranada and Madrid
Period9/07/1413/07/14

Keywords

  • ANN
  • Authorship Attribution
  • DRSA
  • Decision Algorithm
  • Decision Rule
  • Feature Selection
  • Ranking
  • Rule Filtering
  • Stylometry

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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