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Ensemble feature ranking for shellfish farm closure cause identification

Citation

Rahman, A and D'Este, CE and McCulloch, J, Ensemble feature ranking for shellfish farm closure cause identification, Proceedings of MLSDA 2013, 3 December 2013, Dunedin, New Zealand, pp. 13-18. ISBN 978-1-4503-2513-4 (2013) [Refereed Conference Paper]


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Copyright Statement

Copyright 2013 ACM

Official URL: http://www.covic.otago.ac.nz/MLSDA13/

DOI: doi:10.1145/2542652.2542655

Abstract

Shellfish farms must be closed if there is suspected contamination during production to avoid serious health hazards. The authorities monitor a number of environmental and water quality variables through a set of sensors to check the health of shellfish farms and to decide on the closure of the farms. The research presented in this paper aims to develop an ensemble feature ranking algorithm to identify the cause of closure. We have presented and analysed the results obtained using the proposed algorithm to demonstrate its effectiveness.

Item Details

Item Type:Refereed Conference Paper
Keywords:shellfish farm closure, sensor data analysis, machine learning
Research Division:Information and Computing Sciences
Research Group:Artificial Intelligence and Image Processing
Research Field:Expert Systems
Objective Division:Animal Production and Animal Primary Products
Objective Group:Fisheries - Aquaculture
Objective Field:Aquaculture Molluscs (excl. Oysters)
Author:D'Este, CE (Dr Claire D'Este)
ID Code:116721
Year Published:2013
Deposited By:Computing and Information Systems
Deposited On:2017-05-17
Last Modified:2017-06-21
Downloads:0

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