Package: CompositionalML 1.0
Michail Tsagris
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>.
Authors:
CompositionalML_1.0.tar.gz
CompositionalML_1.0.tar.gz(r-4.5-noble)CompositionalML_1.0.tar.gz(r-4.4-noble)
CompositionalML_1.0.tgz(r-4.4-emscripten)CompositionalML_1.0.tgz(r-4.3-emscripten)
CompositionalML.pdf |CompositionalML.html✨
CompositionalML/json (API)
# Install 'CompositionalML' in R: |
install.packages('CompositionalML', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 8 months agofrom:81c2725e38. Checks:OK: 2. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Oct 11 2024 |
R-4.5-linux | OK | Oct 11 2024 |
Exports:alfa.borutaalfa.ppralfa.rfalfa.svmalfappr.tunealfarf.tunealfasvm.tune
Dependencies:BHbigassertrbigparallelrbigstatsrbitbootBorutaclasscliclustercodetoolscolorspaceCompositionalcowplotdoParallele1071emplikenergyfansifarverffflockforeachggplot2glmnetgluegslgtableisobanditeratorslabelinglatticelifecyclemagrittrMASSMatrixMatrixModelsmdamgcvminpack.lmmixturemnormtmunsellmvhtestsnlmennetnumDerivparallellypillarpkgconfigproxypsquadprogquantregR6rangerRColorBrewerRcppRcppArmadilloRcppEigenRcppGSLRcppParallelRcppZigguratregdaRfastRfast2RhpcBLASctlrlangrmioRnanoflannRSpectrascalesshapesnSparseMsurvivaltibbleutf8vctrsviridisLitewithr
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Machine Learning with Compositional Data | CompositionalML-package |
alpha-PPR with compositional predictor variables | alfa.ppr |
alpha-Boruta variable selection | alfa.boruta |
alpha-RF | alfa.rf |
alpha-SVM | alfa.svm |
Tuning the parameters of thealpha-PPR | alfappr.tune |
Tuning the parameters of the alpha-RF | alfarf.tune |
Tuning the parameters of the alpha-SVM | alfasvm.tune |