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  "Title": "Machine Learning with Compositional Data",
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  "Date": "2024-03-13",
  "Authors@R": "person(\"Michail\", \"Tsagris\", role = c(\"aut\", \"cre\"), email = \"mtsagris@uoc.gr\")",
  "Author": "Michail Tsagris [aut, cre]",
  "Maintainer": "Michail Tsagris <mtsagris@uoc.gr>",
  "Description": "Machine learning algorithms for predictor variables that\nare compositional data and the response variable is either\ncontinuous or categorical. Specifically, the Boruta variable\nselection algorithm, random forest, support vector machines and\nprojection pursuit regression are included. Relevant papers\ninclude: Tsagris M.T., Preston S. and Wood A.T.A. (2011). \"A\ndata-based power transformation for compositional data\". Fourth\nInternational International Workshop on Compositional Data\nAnalysis. <doi:10.48550/arXiv.1106.1451> and Alenazi, A.\n(2023). \"A review of compositional data analysis and recent\nadvances\". Communications in Statistics--Theory and Methods,\n52(16): 5535--5567. <doi:10.1080/03610926.2021.2014890>.",
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  "Date/Publication": "2024-03-15 02:30:46 UTC",
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