Semi-automated data classification with feature weighted self organizing map

Andrew Starkey, Aliyu Usman Ahmad

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper presents a Feature Weighted Self-Organizing Map (FWSOM) that analyses the topology information of a converged standard Self organizing Map (SOM) to automatically guide the selection of important inputs during training for improved classification of data with irrelevant inputs. We demonstrate an improved classification accuracy with the proposed method by comparison with the standard SOM and other relevant existing classifiers on synthetic and real-world datasets. In addition, the FWSOM method was able to successfully identify the relevant features which in turn were able to improve the classification performance of the other classification methods.

Original languageEnglish
Title of host publicationICNC-FSKD 2017 - 13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages136-141
Number of pages6
ISBN (Electronic)9781538621653
ISBN (Print)978-1-5386-2166-0
DOIs
Publication statusPublished - 25 Jun 2018
Event13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery, ICNC-FSKD 2017 - Guilin, Guangxi, China
Duration: 29 Jul 201731 Jul 2017

Conference

Conference13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery, ICNC-FSKD 2017
CountryChina
CityGuilin, Guangxi
Period29/07/1731/07/17

Fingerprint

Data Classification
Self organizing maps
Self-organizing Map
Standard Map
Classifiers
Classifier
Topology
Self-organizing map
Demonstrate

Keywords

  • Automation
  • Classification
  • Feature Weighting
  • Self Organizing Maps

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications
  • Hardware and Architecture
  • Information Systems
  • Information Systems and Management
  • Logic
  • Modelling and Simulation
  • Statistics and Probability

Cite this

Starkey, A., & Ahmad, A. U. (2018). Semi-automated data classification with feature weighted self organizing map. In ICNC-FSKD 2017 - 13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (pp. 136-141). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/FSKD.2017.8392964

Semi-automated data classification with feature weighted self organizing map. / Starkey, Andrew; Ahmad, Aliyu Usman.

ICNC-FSKD 2017 - 13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery. Institute of Electrical and Electronics Engineers Inc., 2018. p. 136-141.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Starkey, A & Ahmad, AU 2018, Semi-automated data classification with feature weighted self organizing map. in ICNC-FSKD 2017 - 13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery. Institute of Electrical and Electronics Engineers Inc., pp. 136-141, 13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery, ICNC-FSKD 2017, Guilin, Guangxi, China, 29/07/17. https://doi.org/10.1109/FSKD.2017.8392964
Starkey A, Ahmad AU. Semi-automated data classification with feature weighted self organizing map. In ICNC-FSKD 2017 - 13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery. Institute of Electrical and Electronics Engineers Inc. 2018. p. 136-141 https://doi.org/10.1109/FSKD.2017.8392964
Starkey, Andrew ; Ahmad, Aliyu Usman. / Semi-automated data classification with feature weighted self organizing map. ICNC-FSKD 2017 - 13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 136-141
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