Michela Leonardi, Margherita Colucci, Andrea Vittorio Pozzi, Eleanor M. L. Scerri, Andrea Manica
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引用次数: 0
摘要
在物种分布建模（SDM）中，通常的做法是探索多种机器学习（ML）算法，并将其结果组合成集合。在 R 语言中，有许多不同 ML 算法的实现方法，但由于它们大多是独立开发的，因此经常使用不一致的语法和数据结构。因此，使用多种算法重复分析并将其结果组合起来是一项挑战。专门的 SDM 软件包可以解决这个问题，它通过封装原始函数来提供更简单、统一的界面，以满足各种特定要求。然而，创建和维护这样的界面非常耗时，而且采用这种方法，用户无法轻松集成可能出现的其他方法。tidymodels 提供了标准化的语法、数据结构和建模接口，以及文档齐全的基础设施，可用于集成新算法和度量标准。tidymodels 的广泛采用意味着大多数 ML 算法和度量标准已经集成，用户可以添加其他算法和度量标准。此外，由于 tidymodels 被广泛采用，新的统计方法往往能很快实施，从而很容易集成到现有的管道和分析中。tidysdm 利用 tidymodels 的优势，提供了一个灵活、完全可定制的管道，以适应 SDM。它包括 SDM 专用算法和指标，以及便于在 tidymodels 中使用空间数据的方法。此外，tidysdm 还是第一款允许使用不同时期数据进行 SDM 的软件，为古生物学、考古学、古生物学、古生态学和其他关注过去的学科的学者提供了 SDM 的更多可能性。
期刊介绍：
A British Ecological Society journal, Methods in Ecology and Evolution (MEE) promotes the development of new methods in ecology and evolution, and facilitates their dissemination and uptake by the research community. MEE brings together papers from previously disparate sub-disciplines to provide a single forum for tracking methodological developments in all areas.
MEE publishes methodological papers in any area of ecology and evolution, including:
-Phylogenetic analysis
-Statistical methods
-Conservation & management
-Theoretical methods
-Practical methods, including lab and field
-This list is not exhaustive, and we welcome enquiries about possible submissions. Methods are defined in the widest terms and may be analytical, practical or conceptual.
A primary aim of the journal is to maximise the uptake of techniques by the community. We recognise that a major stumbling block in the uptake and application of new methods is the accessibility of methods. For example, users may need computer code, example applications or demonstrations of methods.
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