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classmap (version 1.2.6)

Visualizing Classification Results

Description

Tools to visualize the results of a classification or a regression. The graphical displays include stacked plots, silhouette plots, quasi residual plots, class maps, predictions plots, and predictions correlation plots. Implements the techniques described and illustrated in Raymaekers J., Rousseeuw P.J., Hubert M. (2022). Class maps for visualizing classification results. \emph{Technometrics}, 64(2), 151–165. \doi{10.1080/00401706.2021.1927849} (open access), Raymaekers J., Rousseeuw P.J.(2022). Silhouettes and quasi residual plots for neural nets and tree-based classifiers. \emph{Journal of Computational and Graphical Statistics}, 31(4), 1332–1343. \doi{10.1080/10618600.2022.2050249}, and Rousseeuw, P.J. (2025). Explainable Linear and Generalized Linear Models by the Predictions Plot. (open access). Examples can be found in the vignettes: "Discriminant_analysis_examples","K_nearest_neighbors_examples", "Support_vector_machine_examples", "Rpart_examples", "Random_forest_examples", "Neural_net_examples", and "predsplot_examples".

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Version

Install

install.packages('classmap')

Monthly Downloads

350

Version

1.2.6

License

GPL (>= 2)

Maintainer

Jakob Raymaekers

Last Published

July 14th, 2025

Functions in classmap (1.2.6)

data_bookReviews

Amazon book reviews data
qresplot

Draw a quasi residual plot of PAC versus a data feature
stackedplot

Make a vertically stacked mosaic plot of class predictions.
vcr.knn.train

Carry out a k-nearest neighbor classification on training data, and prepare to visualize its results.
vcr.forest.newdata

Prepare for visualization of a random forest classification on new data.
vcr.da.newdata

Carry out discriminant analysis on new data, and prepare to visualize its results.
vcr.knn.newdata

Carry out a k-nearest neighbor classification on new data, and prepare to visualize its results.
vcr.neural.newdata

Prepare for visualization of a neural network classification on new data.
vcr.da.train

Carry out discriminant analysis on training data, and prepare to visualize its results.
vcr.forest.train

Prepare for visualization of a random forest classification on training data
vcr.svm.train

Prepare for visualization of a support vector machine classification on training data.
vcr.neural.train

Prepare for visualization of a neural network classification on training data.
silplot

Draw the silhouette plot of a classification
vcr.rpart.train

Prepare for visualization of an rpart classification on training data.
vcr.svm.newdata

Prepare for visualization of a support vector machine classification on new data.
vcr.rpart.newdata

Prepare for visualization of an rpart classification on new data.
makeFV

Constructs feature vectors from a kernel matrix.
data_floralbuds

Floral buds data
predsplot

Make a predictions plot
data_instagram

Instagram data
classmap

Draw the class map to visualize classification results.
predscor

Draws a predictions correlation plot, which visualizes the correlations between the prediction terms in a regression fit.
confmat.vcr

Build a confusion matrix from the output of a function vcr.*.*.
makeKernel

Compute kernel matrix
data_titanic

Titanic data