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.


Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.


0.1.0 by Javier Portela, 7 months ago

Browse source code at

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