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Nine tips for ecologists using machine learning

  • arXiv (Cornell University)
  • Cornell University
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Abstract

Due to their high predictive performance and flexibility, machine learning models are an appropriate and efficient tool for ecologists. However, implementing a machine learning model is not yet a trivial task and may seem intimidating to ecologists with no previous experience in this area. Here we provide a series of tips to help ecologists in implementing machine learning models. We focus on classification problems as many ecological studies aim to assign data into predefined classes such as ecological states or biological entities. Each of the nine tips identifies a common error, trap or challenge in developing machine learning models and provides recommendations to facilitate their use in ecological studies.

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Publication details

DOI
10.48550/arxiv.2305.10472
OpenAlex
W4377121650
Document type
preprint
Language
EN
Source
arXiv (Cornell University)
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