A quick tour of ppgmmga

Alessio Serafini, Luca Scrucca

15 Oct 2018

Introduction

An R package implementing a Projection Pursuit algorithm based on finite Gaussian mixtures models for density estimation using Genetic Algorithms to maximise an approximated Negentropy index. The ppgmmga algorithm provides a method to visualise high-dimensional data in a lower-dimensional space.

library(ppgmmga)
##    ___  ___  ___ ___ _  __ _  ___ ____ _
##   / _ \/ _ \/ _ `/  ' \/  ' \/ _ `/ _ `/
##  / .__/ .__/\_, /_/_/_/_/_/_/\_, /\_,_/ 
## /_/  /_/   /___/            /___/       version 1.0.1

Banknote data

library(mclust)
## Package 'mclust' version 5.4.1
## Type 'citation("mclust")' for citing this R package in publications.
data("banknote")
X <- banknote[,-1]
Class <- banknote$Status
table(Class)
## Class
## counterfeit     genuine 
##         100         100
clPairs(X, classification = Class)

ppgmmga

1-dimensional ppgmmga

2-dimensional ppgmmga

3-dimensional ppgmmga

References

Scrucca, L. and Serafini, A. (2018) Projection pursuit based on Gaussian mixtures and evolutionary algorithms. Under review.