'bugs.R' 'classify.R' 'gpcm.rc.R' 'prob_functions.R'
'scores.R' 'w_lord.R'

Rcpp (>= 0.9.10), plyr, ggplot2, lattice, methods, R2jags,
reshape2

Visualizing Classification Results by Classmaps
c(
person(given="Jakob",family="Raymaekers", role = c("aut","cre"),
email="jakob.raymaekers@kuleuven.be"),
person(given="Peter",family="Rousseeuw", role = c("aut"))
)
Jakob Raymaekers [aut, cre],
Peter Rousseeuw [aut]
stats, graphics, ggplot2, robustbase, e1071, cellWise,
cluster, kernlab, gridExtra
Tools to visualize the results of a classification obtained by discriminant analysis,
k-nearest neighbors, and support vector machines, for two or more classes.
Implements the techniques described and illustrated in
Raymaekers, Rousseeuw and Hubert (2021),
Class maps for visualizing classification results, Technometrics, to appear.
In addition to class maps, also stacked plots are made. Examples can be found in the vignettes:
"Discriminant_analysis_examples","K_nearest_neighbors_examples" and
"Support_vector_machine_examples".

stats, graphics, ggplot2, robustbase, e1071, cellWise,
cluster, kernlab, gridExtra, rpart, randomForest
Tools to visualize the results of a classification of cases.
The graphical displays include stacked plots, silhouette plots, quasi residual plots, and class maps.
Implements the techniques described and illustrated in Raymaekers, Rousseeuw and Hubert (2021),
Class maps for visualizing classification results, Technometrics, appeared online.
<doi:10.1080/00401706.2021.1927849> (open access) and Raymaekers and Rousseeuw (2021),
Silhouettes and quasi residual plots for neural nets and tree-based classifiers,
<arXiv:2106.08814>. Examples can be found in the vignettes: "Discriminant_analysis_examples","K_nearest_neighbors_examples",
"Support_vector_machine_examples", "Rpart_examples", "Random_forest_examples",
and "Neural_net_examples".

knitr, reshape2, svd, rpart.plot, nnet, robCompositions
Tools to visualize the results of a classification of cases.
The graphical displays include stacked plots, silhouette plots, quasi residual plots, and class maps.
Implements the techniques described and illustrated in Raymaekers, Rousseeuw and Hubert (2021), Class maps for visualizing classification results, Technometrics, appeared online.
<doi:10.1080/00401706.2021.1927849> (open access) and Raymaekers and Rousseeuw (2021),
Silhouettes and quasi residual plots for neural nets and tree-based classifiers,
<arXiv:2106.08814>. Examples can be found in the vignettes:
"Discriminant_analysis_examples","K_nearest_neighbors_examples",
"Support_vector_machine_examples", "Rpart_examples", "Random_forest_examples",
and "Neural_net_examples".