Population Assignment using Genetic, Non-Genetic or Integrated Data in a Machine Learning Framework R package assignPOP version 1.3.1 Use Monte-Carlo and K-fold cross-validation coupled with machine- learning classification algorithms to perform population assignment, with functionalities of evaluating discriminatory power of independent training samples, identifying informative loci, reducing data dimensionality for genomic data, integrating genetic and non-genetic data, and visualizing results. Software Depends: R (>= 2.3.2) Imports: caret, doParallel, e1071, foreach, ggplot2, MASS, parallel, randomForest, reshape2, stringr, tree, rlang, Suggests: gtable, iterators, klaR, stringi, knitr, rmarkdown, testthat Kuan-Yu (Alex) Chen <alexkychen@gmail.com> Comprehensive R Archive Network (CRAN) Kuan-Yu (Alex) Chen [aut, cre], Elizabeth A. Marschall [aut], Michael G. Sovic [aut], Anthony C. Fries [aut], H. Lisle Gibbs [aut], Stuart A. Ludsin [aut] GPL (>= 2) 2025-09-12 application/tgz https://CRAN.R-project.org/package=assignPOP doi:10.32614/CRAN.package.assignPOP