earth, randomForest, PresenceAbsence, lattice, graphics,

Title: Collection of Datasets Pertaining to Loop 1 "Mopac"
Authors@R: person("Scott", "McKenzie", email = "sccmckenzie@gmail.com",
Description: Provides real & simulated datasets containing time-series traffic observations
and additional information pertaining to Loop 1 "Mopac" located in Austin, Texas.
Suggests: dplyr, lubridate, tibble, readr, hms

Title: MOPSOCD: Multi-objective Particle Swarm Optimization with
Description: A multi-objective optimization solver based on particle
swarm optimization with crowding distance.
Packaged: 2013-06-04 09:21:29 UTC; Pros Naval

Title: Morphological Analysis for Japanese
Description: Supports morphological analysis for Japanese by using 'MeCab'.
Can input data.frame and obtain all results of 'MeCab' and row number of
Imports: dplyr, magrittr, purrr, rlang, stringr, tibble, tidyr
Suggests: knitr, rmarkdown, stringi, testthat (>= 3.0.0), tidyverse
Packaged: 2022-03-30 05:28:50 UTC; matsumura

Packaged: 2022-05-06 01:09:00 UTC; matsumura

Imports: dplyr, ggplot2, ggraph, igraph, magrittr, purrr, rlang, stats,
Packaged: 2022-07-12 01:36:40 UTC; matsumura

Title: A Toolbox for Conditional Inference Random Forests
Imports: partykit, varImp, plyr, foreach, measures, methods, MASS, iml
Description: Additions to 'party' package : tools for the interpretation of forests (surrogate trees, prototypes, etc.), feature selection (see Gregorutti et al (2017) <arXiv:1310.5726>, Hapfelmeier and Ulm (2013) <doi:10.1016/j.csda.2012.09.020>, Altmann et al (2010) <doi:10.1093/bioinformatics/btq134>) and parallelized versions of conditional forest and variable importance functions.

Imports: partykit, varImp, plyr, foreach, measures, methods, MASS, iml,
Suggests: doParallel, knitr, rmarkdown, rmdformats, GDAtools,
RColorBrewer, caret, pROC, tidyverse, e1071

Title: A Toolbox for Conditional Inference Trees and Random Forests
pdp, vip, ggplot2, rlang, shiny, shinyWidgets, rclipboard, DT,
Description: Additions to 'party' and 'partykit' packages : tools for the interpretation of forests (surrogate trees, prototypes, etc.), feature selection (see Gregorutti et al (2017) <arXiv:1310.5726>, Hapfelmeier and Ulm (2013) <doi:10.1016/j.csda.2012.09.020>, Altmann et al (2010) <doi:10.1093/bioinformatics/btq134>) and parallelized versions of conditional forest and variable importance functions. Also modules and a shiny app for conditional inference trees.