The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.
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 (≥ 7.3.51.4), magrittr, FactoMineR (≥ 2.3), ggplot2 (≥ 3.3.0), mltools, dplyr, data.table, MBA, pROC, ggrepel |
Suggests: | knitr, markdown, egg |
Published: | 2020-10-24 |
Author: | Javier Portela [aut, cre] |
Maintainer: | Javier Portela <javipgm at gmail.com> |
License: | GPL (≥ 3) |
NeedsCompilation: | no |
CRAN checks: | visualpred results |
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: visualpred_0.1.0.zip, r-release: visualpred_0.1.0.zip, r-oldrel: visualpred_0.1.0.zip |
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 |
Please use the canonical form https://CRAN.R-project.org/package=visualpred to link to this page.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.