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

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  • Crisci, C.
  • Ghattas, B.
  • Perera, G.

Abstract

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.

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  • Crisci, C. & Ghattas, B. & Perera, G., 2012. "A review of supervised machine learning algorithms and their applications to ecological data," Ecological Modelling, Elsevier, vol. 240(C), pages 113-122.
    • Handle: RePEc:eee:ecomod:v:240:y:2012:i:c:p:113-122
    DOI: 10.1016/j.ecolmodel.2012.03.001
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