Estimación del plano anestésico en elefante marinos del sur utilizando técnicas de Machine Learning

• Main Authors: Zàrate, Marcos, Lewis, Mirtha Noemí
• Format: Conference Object
• Language: Spanish
• Published: 2016
• Subjects: Ciencias Informáticas; Inteligencia Artificial; WEKA; ecología del paisaje; Data mining; Elefante; Plano; Elephant Seal; Southern Elephant Seal
• Online Access: http://hdl.handle.net/10915/56749

Prediction systems are techniques that build and study new forecasts through a branch of the artificial intelligence called Machine Learning. In this work we intend to estimate the time that remains anesthetized an 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 algorithms used particular classification algorithms were compared J4.8, SMO, Random Tree, NBTree 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, making this an accuracy of 98.79%. XIII Workshop Bases de datos y Minería de Datos (WBDMD). Red de Universidades con Carreras en Informática (RedUNCI)