Related papers: Nine tips for ecologists using machine learning

Nine tips for ecologists using machine learning

URL: http://arxiv.org/abs/2305.10472v2
Date: Fri, 26 May 2023 07:38:55 GMT
Title: Nine tips for ecologists using machine learning
Authors: Marine Desprez, Vincent Miele and Olivier Gimenez
Abstract summary: We focus on classification problems as many ecological studies aim to assign data into 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.
Score: 0.0
License: http://creativecommons.org/licenses/by-nc-sa/4.0/
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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