person("Gary", "Hutson", , "hutsons-hacks@outlook.com", c("aut", "cre"), comment = c(ORCID="0000-0003-3534-6143"))
Description: Takes the outputs of a 'caret' confusion matrix and allows for the quick conversion of these list items to lists.
The intended usage is to allow the tool to work with the outputs of machine learning classification models.
This tool works with classification problems for binary and multi-classification problems and allows for the record level conversion of the confusion matrix outputs.
This is useful, as it allows quick conversion of these objects for storage in database systems and to track ML model performance over time.
Traditionally, this approach has been used for highlighting model representation and feature slippage.
Imports: dplyr, tidyr, magrittr, caret, mlbench, lattice, scales,
Author: Gary Hutson [aut, cre] (<https://orcid.org/0000-0003-3534-6143>)

ggplot2, e1071, randomForest, purrr, furrr

Imports: dplyr, tidyr, magrittr, caret, purrr, furrr
Suggests: knitr, rmarkdown, e1071, randomForest, scales, mlbench

Suggests: knitr, rmarkdown, e1071, randomForest, scales, mlbench,

Title: Distance metrics for trees generated by Congreve and Lamsdell
Description: Includes the 100 datasets simulated by Congreve and Lamsdell (2016)
<doi:10.1111/pala.12236>, and analyses of the partition and quartet distance of
reconstructed trees from the generative tree, as analysed by Smith (2019)
person(given = "Curtis R.", family="Congreve", role = c("cph", "dtc")),
person('James C.', 'Lamsdell', role=c("cph", "dtc"))
Copyright: Data from Congreve & Lamsdell (2016) released under a CC0
Suggests: ape, bookdown, knitr, phangorn, Quartet, rmarkdown,
Maintainer: Martin R. Smith <martin.smith@durham.ac.uk>

Title: Distance Metrics for Trees Generated by Congreve and Lamsdell

Title: Flexible Tools for Multiple Imputation
Description: Provides a set of tools that can be used across 'data.frame' and

Title: A package to check the cancellation axioms of conjoint
Depends: R (>= 2.14.0), parallel, methods
Description: Implementation of a procedure (Domingue, 2012; see also
Karabatsos, 2001 and Kyngdon, 2011) to test the single and
double cancellation axioms of conjoint measure in data that is
dichotomously coded and measured with error.