DESCRIPTION

Package: RCschratz2019
Title: Research Compendium package for the publication
    "Monitoring forest health using hyperspectral imagery: Does feature selection improve the performance of machine-learning techniques?"
Version: 0.0.0.9000
Authors@R:
    person(given = "Patrick",
           family = "Schratz",
           role = c("aut", "cre"),
           email = "patrick.schratz@gmail.com",
           comment = c(ORCID = "0000-0003-0748-6624"))
Description: Provides functions for the referenced study
License: MIT + file LICENSE
URL: https://github.com/pat-s/2019-feature-selection
BugReports:
    https://github.com/pat-s/2019-feature-selection/issues
Imports:
    cli,
    curl,
    data.table,
    dplyr,
    drake,
    forcats,
    fs,
    furrr,
    future,
    future.apply,
    future.callr,
    getSpatialData,
    ggplot2,
    ggpubr,
    ggspatial,
    glue,
    hsdar,
    knitr,
    magrittr,
    mapview,
    mlrMBO,
    parallelMap,
    pbmcapply,
    purrr,
    R.utils,
    raster,
    rgenoud,
    sf,
    stringr,
    usethis
Remotes:
    16EAGLE/getSpatialData,
    pat-s/hsdar@9de91c8f67c4b19b39bca7d2c03d37d7641b2b33
ByteCompile: true
Encoding: UTF-8
LazyData: true
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.0.2