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 <tkcaccia@gmail.com>
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: 2026-06-16 10:09:53 UTC; root
NeedsCompilation: yes
Author: Stefano Cacciatore [aut, trl, cre]
        (<https://orcid.org/0000-0001-7052-7156>), Leonardo Tenori
        [aut] (<https://orcid.org/0000-0001-6438-059X>)
Config/pak/sysreqs: libpng-dev libssl-dev python3
Repository: https://tkcaccia.r-universe.dev
Date/Publication: 2026-03-17 14:11:46 UTC
RemoteUrl: https://github.com/tkcaccia/kodama
RemoteRef: HEAD
RemoteSha: d2dbe30ee66509b82c084616d6961c5b292cd059