Feature significance for multivariate kernel density estimation
Tarn Duong <tduong@pasteur.fr> & Matt Wand <wand@uow.edu.au>

Tarn Duong <tarn.duong@gmail.com> & Matt Wand <wand@uow.edu.au>

Tarn Duong <tduong@maths.unsw.edu.au> & Matt Wand <wand@maths.unsw.edu.au>

Tarn Duong <tarn.duong@gmail.com> & Matt Wand <Matt.Wand@uts.edu.au>

Local Inferential Feature Significance for Multivariate Kernel
Density Estimation
grDevices, graphics, ks (>= 1.8.0), misc3d, rgl, stats, tcltk
Local inferential feature significance for multivariate kernel density estimation.

grDevices, graphics, ks (>= 1.10.0), misc3d, rgl, stats, tcltk

c(person("Tarn", "Duong", role=c("aut","cre"), email="tarn.duong@gmail.com"),
person("Matt", "Wand", role="aut", email="Matt.Wand@uts.edu.au"))

Feature significance for multivariate kernel density
estimation

Measurement Level Independent Feature Correlation Matrix
c(person("Guido", "Moeser", role = c("aut", "cre"),
email = "guido.moeser@masem.de"),
person("Ilja", "Muhl", role = "aut"))
Uses three different correlation coefficients to
calculate measurement-level adequate correlations in a feature matrix:
Pearson product-moment correlation coefficient,
Intraclass correlation and Cramer's V.
Guido Moeser [aut, cre],
Ilja Muhl [aut]

person("Richard", "Davis", email = "davisconsulting@gmail.com", role = c("aut", "cre"))
Finds modelling features through a detailed analysis of model residuals using 'rpart' classification and regression trees. Scans the residuals of a model across subsets of the data to identify areas where the model prediction differs from the actual target variable. S. Chatterjee, A. S. Hadi (2006) <doi:10.1002/0470055464>.
png, knitr, Metrics, mlr, gbm, randomForest

rpart, rpart.plot, utils, plyr, grDevices

Turn Features On and Off using Feature Flags
person(given = "Ryszard",
family = "Szymański",
role = c("aut", "cre"),
email = "ryszard.szymanski@outlook.com")
Feature flags allow developers to turn features of their
software on and off in form of configuration. This package provides
functions for creating feature flags in code. It exposes an interface
for defining own feature flags which are enabled based on custom criteria.