Maximum Entropy machine learning model output using digitized downed trees (structure) with three variables and regularization multiplier of 7.0
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https://dataverse.tdl.org/citation?persistentId=doi:10.18738/T8/ILRKFQ
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资源简介：
<p> This dataset (multiple outputs files in a compresssed folder) is output from a run of the Maxent ML Model (Phillips et.al., 2006, url: https://biodiversityinformatics.amnh.org/open_source/maxent/) using trees with structure (N=4283) and includes the three environmental variables with most contribution according to MaxentVariableSelection (Jueterbock, et.al. 2016) (vegetation community, inundation probability, and soil classification) and implemented as hinge features with a regularization multiplier (beta parameter) of 7.0. The value of 0p150 in the dataset file names refer to the fact that it uses digitized downed trees with structure. </p>
<p> Phillips, S.J., Anderson, R.P., Schapire, R.E. (2006). Maximum Entropy modelling of species geographic distribution. Ecological Modelling, 190, 231-259.</p>
<p> Jueterbock, A. Smolina, I., Cover, J.A., Hoaru, C. (2016) The fate of arctic seaweed Fucus disticus under climate change: an ecological niche modelling approach. Ecology and Evolution, 6(6), 1712-1724.</p>
提供机构：
Texas Data Repository
创建时间：
2020-06-09
