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Estimate of the Anesthesia Stage in Southern Elephant Seals using WEKA Data Mining Tool

M. D. Zárate, M. N. Lewis. Published in Information Science

International Journal of Applied Information Systems
Year of Publication: 2016
Publisher: Foundation of Computer Science (FCS), NY, USA
Authors:M. D. Zárate, M. N. Lewis
10.5120/ijais2016451603
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  1. M D Zarate and M N Lewis. Estimate of the Anesthesia Stage in Southern Elephant Seals using WEKA Data Mining Tool. International Journal of Applied Information Systems 11(4):48-52, September 2016. URL, DOI BibTeX

    @article{10.5120/ijais2016451603,
    	author = "M. D. Zarate and M. N. Lewis",
    	title = "Estimate of the Anesthesia Stage in Southern Elephant Seals using WEKA Data Mining Tool",
    	journal = "International Journal of Applied Information Systems",
    	issue_date = "September 2016",
    	volume = 11,
    	number = 4,
    	month = "Sep",
    	year = 2016,
    	issn = "2249-0868",
    	pages = "48-52",
    	numpages = 5,
    	url = "http://www.ijais.org/archives/volume11/number4/938-2016451603",
    	doi = "10.5120/ijais2016451603",
    	publisher = "Foundation of Computer Science (FCS), NY, USA",
    	address = "New York, USA"
    }
    

Abstract

Prediction systems are techniques that build and study new forecasts through a branch of the artificial intelligence called Machine Learning. In this work it is estimate the time that remains anesthetized a southern elephant seal to which you have applied a combination of drugs (Zoletil®), the fundamental objective of anesthesia is to avoid risky situations to researchers studying this species. To know these times, data mining techniques and classification algorithms are used, particularly algorithms it were compared J48, SMO, Random Tree, NB Tree y Naïve Bayes with data mining tool WEKA and a data set containing the records of 96 individuals undergoing anesthesia procedure. It is concluded that after tests (Random Tree) was the classification algorithm that best responded, with an accuracy of 98. 79%.

Reference

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Keywords

Classification, Machine Learning, WEKA, Anesthesia, Mirounga leonina