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.


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install.packages("visualpred")

0.1.0 by Javier Portela, a month ago


Browse source code at https://github.com/cran/visualpred


Authors: Javier Portela [aut, cre]


Documentation:   PDF Manual  


GPL (>= 3) license


Imports gbm, randomForest, nnet, e1071, MASS, magrittr, FactoMineR, ggplot2, mltools, dplyr, data.table, MBA, pROC, ggrepel

Suggests knitr, markdown, egg


See at CRAN