Package: KODAMA Version: 3.3 Date: 2026-03-17 Authors@R: c(person("Stefano", "Cacciatore", role = c("aut", "trl", "cre"),email = "tkcaccia@gmail.com", comment = c(ORCID = "0000-0001-7052-7156")), person("Leonardo", "Tenori", role = "aut",email = "tenori@cerm.unifi.it", comment = c(ORCID = "0000-0001-6438-059X"))) Maintainer: Stefano Cacciatore Title: Knowledge Discovery by Accuracy Maximization Description: A self-guided, weakly supervised learning algorithm for feature extraction from noisy and high-dimensional data. It facilitates the identification of patterns that reflect underlying group structures across all samples in a dataset. The method incorporates a novel strategy to integrate spatial information, improving the clarity of results in spatially resolved data. Depends: R (>= 2.10.0), stats, Rtsne, umap Imports: Rcpp (>= 0.12.4), Rnanoflann, methods, Matrix LinkingTo: Rcpp, RcppArmadillo, Rnanoflann, Matrix Suggests: rgl, knitr, rmarkdown, testthat (>= 3.0.0) VignetteBuilder: knitr SuggestsNote: No suggestions LazyData: true LazyDataCompression: xz Config/testthat/edition: 3 License: GPL (>= 2) Packaged: 2026-10-27 08:05:59 UTC; root NeedsCompilation: yes Author: Stefano Cacciatore [aut, trl, cre] (ORCID: ), Leonardo Tenori [aut] (ORCID: ) Repository: https://cran.r-universe.dev Date/Publication: 2026-03-17 15:30:02 UTC RemoteUrl: https://github.com/cran/KODAMA RemoteRef: HEAD RemoteSha: 66ba26a3fc6de2d15fb4c1f4e72e7e7567ecb684