Logistic Biplot Estimation Using Machine Learning Algorithms R package BiplotML version 1.1.1 Implements methods for fitting logistic biplot models to multivariate binary data. The logistic biplot represents individuals as points and binary variables as directed vectors in a low-dimensional subspace; the orthogonal projection of each individual onto a variable vector approximates the expected probability that the corresponding characteristic is present. Available fitting methods include conjugate gradient algorithms, a coordinate descent Majorization-Minimization (MM) algorithm, and a block coordinate descent algorithm based on data projection that supports matrices with missing values and allows new individuals to be projected as supplementary rows without refitting the model. A cross-validation procedure is provided to select the number of latent dimensions k. References: Babativa-Marquez and Vicente-Villardon (2021) <doi:10.3390/math9162015>; Vicente-Villardon and Galindo (2006, ISBN:9780470973196). Software Depends: R (>= 4.1.0) Imports: optimx, RSpectra Suggests: testthat (>= 3.0.0), knitr, rmarkdown, dplyr (>= 1.0.0), tidyr (>= 1.1.0), ggplot2 (>= 3.3.2), ggrepel, pracma, mvtnorm Jose Giovany Babativa-Marquez <jgbabativam@unal.edu.co> Comprehensive R Archive Network (CRAN) Jose Giovany Babativa-Marquez [cre, aut] (ORCID: <https://orcid.org/0000-0002-4989-7459>) MIT + file LICENSE (https://CRAN.R-project.org/package=BiplotML/LICENSE) 2026-05-08 application/tgz https://CRAN.R-project.org/package=BiplotML doi:10.32614/CRAN.package.BiplotML