MVPpred lizard ecomorphology machine learning model, data, and code associated with Lailvaux et al. (2022) "Machine learning accurately predicts the multivariate performance phenotype from morphology in lizards", PLoS One.

Name: MVPpred lizard ecomorphology machine learning model, data, and code associated with Lailvaux et al. (2022) "Machine learning accurately predicts the multivariate performance phenotype from morphology in lizards", PLoS One.
Creator: Herrel, Anthony; Wilson, Robbie S.; Kabir, Md Wasi Ul; Pun, Pooja; Lailvaux, Simon; Tamjidul Hoque, Md; Mishra, Avdesh
Published: 2022-01-07 00:00:00
License: 暂无描述

Figshare2022-01-07 更新2026-04-08 收录

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https://figshare.com/articles/dataset/MVPpred_lizard_ecomorphology_machine_learning_model_data_and_code_associated_with_Lailvaux_et_al_2022_Machine_learning_accurately_predicts_the_multivariate_performance_phenotype_from_morphology_in_lizards_PLoS_One_/18029474/1

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资源简介：

This archive contains the working MVPpred machine learning lizard performance model, along with the associated training data, code, and output. The working model and a brief model tutorial are located in the directory Pooja/Userinterface/UI. Note that model operation requires a working version of the Python Anaconda software to be installed on the machine running it. Contact Md Tamjidul Hoque (thoque@uno.edu) or Simon Lailvaux (slailvaux@gmail.com) with any queries or issues.

提供机构：

Herrel, Anthony; Wilson, Robbie S.; Kabir, Md Wasi Ul; Pun, Pooja; Lailvaux, Simon; Tamjidul Hoque, Md; Mishra, Avdesh

创建时间：

2022-01-07