{ "_id": "6a115df8acfb0bcc41ceca0b", "Package": "hetcorFS", "Type": "Package", "Title": "Unsupervised Feature Selection using the Heterogeneous\nCorrelation Matrix", "Version": "1.0.1", "Authors@R": "c(person(given = \"Cristina\",\nfamily = \"Tortora\",\nrole = c(\"aut\", \"cre\", \"fnd\"),\nemail = \"grikris1@gmail.com\"),\nperson(given = \"Antonio\",\nfamily = \"Punzo\",\nrole = \"aut\"),\nperson(given = \"Shaam\",\nfamily = \"Madhvani\",\nrole = \"aut\"))", "Description": "Unsupervised multivariate filter feature selection using\nthe UFS-rHCM or UFS-cHCM algorithms based on the heterogeneous\ncorrelation matrix (HCM). The HCM consists of Pearson's\ncorrelations between numerical features, polyserial\ncorrelations between numerical and ordinal features, and\npolychoric correlations between ordinal features. Tortora C.,\nMadhvani S., Punzo A. (2025). \"Designing unsupervised\nmixed-type feature selection techniques using the heterogeneous\ncorrelation matrix.\" International Statistical Review\n. 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