Machine Learning Classification of Turtle Habitats

This GitHub repository contains the code used in analysis of all datasets used in Cold-adapted Cretaceous polar turtle resolves the trans-Antarctic radiations of Testudinata

by Benjamin P. Kear, Márton Rabi, Martin Kundrát, Michael S. Y. Lee, Daniel Snitting, Peter Trussler, Mohamad Bazzi, Barbara E. Wagstaff, Dorris E. Seegets-Villiers, Thomas H. Rich, Patricia Vickers-Rich & Lesley Kool

Code written and maintained by Mohamad Bazzi

Contact: mohammed_bazzi@hotmail.com

Load the .RData file

Access the study’s .Rdata object, containing all data and results, using: piggyback!

# This R code shows how to access a .Rdata file from a GitHub release using the piggyback package.

# 1. First install and load the piggyback package.
# 2. Create a temporary directory and download the default.RData file from the specified GitHub repository release version using the pb_download() function.
# 3. Finally, load the downloaded .Rdata file into the R environment using the load() function.

# install.packages(piggyback)
# require(piggyback)

# Create temporary directory and load .Rdata into R environment.
# pb_download(file = "default.RData",dest = tempdir(),repo = "mohabazzi/Turtle-Project-2023",tag = "v1.0.0")
# load(file = file.path(tempdir(),"default.RData"))

No token authentication is required.

Data files included:

Measurement File.xlsx - Extant and fossil testudinatan forelimb proportion dataset of Joyce & Gauthier 2004.

Access docker image via Dockerhub
https://hub.docker.com/repository/docker/mohamadbazzi/turtle-image/general