Visual contour and 2D point and contour plots for binary classification modeling under algorithms such as 'glm', 'rf', '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 under the 'XAI' paradigm.
Version: 0.1.1 Depends: R (≥ 3.5.0) Imports: gbm, randomForest, nnet (≥ 7.3.12), e1071, MASS (≥ 7.3.51.4), magrittr, FactoMineR (≥ 2.3), ggplot2 (≥ 3.3.0), mltools, dplyr, data.table, MBA, pROC, ggrepel Suggests: knitr, markdown, egg Published: 2024-11-07 DOI: 10.32614/CRAN.package.visualpred Author: Javier Portela [aut, cre] Maintainer: Javier Portela <javipgm at gmail.com> License: GPL (≥ 3) NeedsCompilation: no Materials: NEWS CRAN checks: visualpred results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=visualpred to link to this page.
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