On-line feature and classifier selection for agricultural produce

S. Laykin, Y. Edan, V. Alchanatis

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

1 Scopus citations

Abstract

This paper presents an on-line hierarchical classifier for agricultural products. The classifier consists of two levels. The first level detects new populations using an on-line clustering algorithm. The second level selects the best-fit classifier using a fuzzy system. This paper presents the combination of the two levels into a complete system. Feature selection is conducted on-line according to the classified population. A synthetic dataset is used to estimate the classifier capabilities and compare it to previous results. Results indicated that the combined online system results in improved classification accuracy.

Original languageEnglish
Title of host publicationProceedings of the Eighth IASTED International Conference On Artificial Intelligence and Soft Computing
EditorsA.P. Pobil
Pages127-131
Number of pages5
StatePublished - 27 Dec 2004
EventProceedings of the Eighth IASTED International Conference on Atificial Intelligence and Soft Computing - Marbella, Spain
Duration: 1 Sep 20043 Sep 2004

Publication series

NameProceedings of the Eighth IASTED International Conference on Artificial Intelligence and Soft Computing

Conference

ConferenceProceedings of the Eighth IASTED International Conference on Atificial Intelligence and Soft Computing
Country/TerritorySpain
CityMarbella
Period1/09/043/09/04

Keywords

  • Classifier selection
  • Fuzzy rule-based system and feature selection
  • Unsupervised classification

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