Package: manydist
Type: Package
Title: Distance-Based Learning for Mixed-Type Data
Version: 0.5.1
Authors@R: c(
    person(given = "Alfonso",
           family = "Iodice D'Enza",
           role = c("aut", "cre"),
           email = "iodicede@unina.it"),
    person(given = "Angelos",
           family = "Markos",
           role = "aut",
           email = "amarkos@gmail.com"),
    person(given = "Michel",
           family = "van de Velden",
           role = "aut"),
    person(given = "Carlo",
           family = "Cavicchia",
           role = "aut"))
Description: Provides tools for constructing, computing, and using distance
    measures for numerical, categorical, and mixed-type data. The package
    implements a flexible framework in which continuous and categorical
    components can be combined under additive, commensurable, and
    association-aware specifications. Supported methods include classical
    distances such as Gower, Euclidean, Manhattan, and Mahalanobis-type
    distances; categorical dissimilarities such as simple matching,
    occurrence-frequency, and association-based measures; and mixed-type
    presets designed to reduce biases due to variable type, scale,
    distribution, redundancy, and number of categories. The package also
    provides scaling options, supervised and unsupervised distance
    constructions, leave-one-variable-out tools for distance-based variable
    importance, and integration with distance-based learning workflows such
    as nearest-neighbour prediction, partitioning around medoids, and
    spectral clustering. Methods are motivated by van de Velden,
    Iodice D'Enza, Markos, and Cavicchia (2026)
    <doi:10.1080/10618600.2026.2680181> and related work on categorical
    and mixed-type dissimilarities.
URL: https://alfonsoiodicede.github.io/manydist_package/,
        https://github.com/alfonsoIodiceDE/manydist_package/tree/main/manydist
BugReports: https://github.com/alfonsoIodiceDE/manydist_package/issues
Imports: aricode, cluster, clusterGeneration, data.table, dials,
        distances, dplyr, entropy, fastDummies, forcats, fpc, generics,
        ggplot2, kdml, magrittr, Matrix, parsnip, philentropy, purrr,
        readr, recipes, Rfast, rlang, rsample, stats, tibble, tidyr,
        tidyselect, tune
Depends: R (>= 4.5.0)
Suggests: arules, clustMixType, FD, klaR, mclust, palmerpenguins,
        parallelDist, StatMatch, testthat (>= 3.0.0), workflows,
        workflowsets
License: GPL-3
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Config/roxygen2/version: 8.0.0
Config/testthat/edition: 3
Packaged: 2026-07-23 15:39:45 UTC; Alfo
Author: Alfonso Iodice D'Enza [aut, cre],
  Angelos Markos [aut],
  Michel van de Velden [aut],
  Carlo Cavicchia [aut]
Maintainer: Alfonso Iodice D'Enza <iodicede@unina.it>
Repository: CRAN
Date/Publication: 2026-07-23 16:10:06 UTC
Built: R 4.7.0; ; 2026-09-01 05:20:32 UTC; windows
