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treeDA (version 0.0.5)

Tree-Based Discriminant Analysis

Description

Performs sparse discriminant analysis on a combination of node and leaf predictors when the predictor variables are structured according to a tree, as described in Fukuyama et al. (2017) .

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Install

install.packages('treeDA')

Monthly Downloads

186

Version

0.0.5

License

GPL-2

Issues

0

Pull Requests

0

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0

Forks

0

Maintainer

Julia Fukuyama

Last Published

May 14th, 2021

Functions in treeDA (0.0.5)

plot_coefficients

Plot the discriminating axes from treeda
plot.treedacv

Plot a treedacv object
nodeToLeafCoefficients

Node coefficients to leaf coefficients
treeDA-package

Tree-based discriminant analysis
treeda

Tree-based sparse discriminant analysis
treeda_example

Example dataset
predict.treeda

Predict using new data
treedacv

treeda cross validation
makeResponseMatrix

Make response matrix
makeNodeAndLeafPredictors

Make a matrix with predictors for each leaf and node
makeLeafCoefficients

Make leaf coefficients
print.treedacv

Print treedacv objects
print.treeda

Print a treeda object
checkPredictorsAndTree

Check predictors
makeClassProperties

Compute properties of the classes
get_leaf_position

Get leaf positions from a tree layout
coef.treeda

Coefficients from treeda fit
combine_plot_and_tree

Method for combining two ggplots
getBranchLengths

Make branch length vector
expand_background

Expand the background of a gtable.
makeDescendantMatrix

Make descendant matrix
edgesToChildren

Makes a hash table with nodes and their children