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On performance of DRSA-ANN classifier

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

6 Citations (Scopus)

Abstract

Rule-based and connectionist classifiers are typically named as two different approaches to recognition tasks. The first relies on induction of a set of rules that list conditions to be met for a decision to be applicable, while the latter means distribution of data and processing. Both solutions give satisfactory results in many classification problems yet their fusion and analysis of performance of the resulting hybrid classifier bring additional observations as to the role of particular features in the recognition. These observations are not based on domain knowledge, but on techniques employed and their inherent properties. The paper presents a study on performance of DRSA-ANN classifier applied within the domain of stylometry, a quantitative analysis of writing styles.

Original languageEnglish
Title of host publicationHybrid Artificial Intelligent Systems - 6th International Conference, HAIS 2011, Proceedings
Pages172-179
Number of pages8
EditionPART 2
DOIs
Publication statusPublished - 2011
Event6th International Conference on Hybrid Artificial Intelligence Systems, HAIS 2011 - Wroclaw, Poland
Duration: 23 May 201125 May 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume6679 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference6th International Conference on Hybrid Artificial Intelligence Systems, HAIS 2011
Country/TerritoryPoland
CityWroclaw
Period23/05/1125/05/11

Keywords

  • ANN
  • Classifier
  • DRSA
  • Feature Selection
  • Stylometry

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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