CompositionalML:Machine Learning with Compositional Data
Machine learning algorithms for predictor variables that are compositional data and the response variable is either
continuous or categorical. Specifically, the Boruta variable
selection algorithm, random forest, support vector machines and
projection pursuit regression are included. Relevant papers
include: Tsagris M.T., Preston S. and Wood A.T.A. (2011). "A
data-based power transformation for compositional data". Fourth
International International Workshop on Compositional Data
Analysis. <doi:10.48550/arXiv.1106.1451> and Alenazi, A.
(2023). "A review of compositional data analysis and recent
advances". Communications in Statistics--Theory and Methods,
52(16): 5535--5567. <doi:10.1080/03610926.2021.2014890>.
