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visualpred (version 0.1.0)

Visualization 2D of Binary Classification Models

Description

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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Version

Install

install.packages('visualpred')

Monthly Downloads

591

Version

0.1.0

License

GPL (>= 3)

Maintainer

Javier Portela

Last Published

October 24th, 2020

Functions in visualpred (0.1.0)

famdcontourlabel

Outliers in Contour plots and FAMD function for classification modeling
mcacontour

Contour plots and MCA function for classification modeling
pima

Pima indian diabetes dataset
breastwisconsin1

Breast Cancer Winsconsin dataset
spiral

spiral sample data
Hmda

Home Mortgage Disclosure Act dataset
mcamodelobis

Basic MCA function for clasification
famdcontour

Contour plots and FAMD function for classification modeling
mcacontourjit

Contour plots and MCA function for classification modeling
nba

nba dataset