visualpred: Visualization 2D of Binary Classification Models

Visual 2D point and contour plots for binary classification modeling under algorithms such as glm(), randomForest(), gbm(), nnet() and svm(), presented over two dimensions generated by FAMD and MCA methods. Package 'FactoMineR' for multivariate reduction functions and package 'MBA' for interpolation functions are used. The package can be used to visualize the discriminant power of input variables and algorithmic modeling, explore outliers, compare algorithm behaviour, etc. It has been created initially for teaching purposes, but it has also many practical uses.

Version: 0.1.0
Depends: R (≥ 3.5.0)
Imports: gbm, randomForest, nnet (≥ 7.3.12), e1071, MASS (≥, magrittr, FactoMineR (≥ 2.3), ggplot2 (≥ 3.3.0), mltools, dplyr, data.table, MBA, pROC, ggrepel
Suggests: knitr, markdown, egg
Published: 2020-10-24
DOI: 10.32614/CRAN.package.visualpred
Author: Javier Portela [aut, cre]
Maintainer: Javier Portela <javipgm at>
License: GPL (≥ 3)
NeedsCompilation: no
CRAN checks: visualpred results [issues need fixing before 2024-07-12]


Reference manual: visualpred.pdf
Vignettes: Advanced settings
visualpred package
Comparing algorithms
Plotting outliers


Package source: visualpred_0.1.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): visualpred_0.1.0.tgz, r-oldrel (arm64): visualpred_0.1.0.tgz, r-release (x86_64): visualpred_0.1.0.tgz, r-oldrel (x86_64): visualpred_0.1.0.tgz


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