Package: manydist
Type: Package
Title: Distance-Based Learning for Mixed-Type Data
Version: 0.5.2
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, 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
Config/pak/sysreqs: cmake make libicu-dev libuv1-dev libx11-dev
Repository: https://alfonsoiodicede.r-universe.dev
Date/Publication: 2026-10-19 11:32:35 UTC
RemoteUrl: https://github.com/alfonsoiodicede/manydist_package
RemoteRef: HEAD
RemoteSha: 53711e475d47628de5f2423f458b2cd21b505825
RemoteSubdir: manydist
Packaged: 2026-10-19 14:11:37 UTC; root
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>