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A review of supervised machine learning algorithms and their applications to ecological data

机译:监督机器学习算法及其在生态数据中的应用综述

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In this paper we present a general overview of several supervised machine learning (ML) algorithms and illustrate their use for the prediction of mass mortality events in the coastal rocky benthic communities of the NW Mediterranean Sea. In the first part of the paper we present, in a conceptual way, the general framework of ML and explain the basis of the underlying theory. In the second part we describe some outstanding ML techniques to treat ecological data. In the third part we present our ecological problem and we illustrate exposed ML techniques with our data. Finally, we briefly summarize some extensions of several methods for multi-class output prediction.
机译:在本文中,我们概述了几种有监督的机器学习(ML)算法,并说明了它们在预测西北地中海沿岸岩石底栖生物群落中的大规模死亡事件中的应用。在本文的第一部分中,我们以概念性的方式介绍了机器学习的一般框架,并解释了基础理论的基础。在第二部分中,我们描述了处理生态数据的一些杰出的机器学习技术。在第三部分中,我们提出了生态问题,并通过数据说明了暴露的机器学习技术。最后,我们简要总结了几种用于多类输出预测的方法的扩展。

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