KODAMA: Knowledge Discovery by Accuracy Maximization

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 interpretability of results in spatially resolved data.

Package details

AuthorStefano Cacciatore [aut, trl, cre] (ORCID: <https://orcid.org/0000-0001-7052-7156>), Leonardo Tenori [aut] (ORCID: <https://orcid.org/0000-0001-6438-059X>)
MaintainerStefano Cacciatore <tkcaccia@gmail.com>
LicenseGPL (>= 2)
Version3.0
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("KODAMA")

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KODAMA documentation built on June 8, 2025, 11:53 a.m.