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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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0.0.5
0.0.4
0.0.3
0.0.2
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Install
install.packages('treeDA')
Monthly Downloads
165
Version
0.0.5
License
GPL-2
Issues
0
Pull Requests
0
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0
Repository
https://github.com/jfukuyama/treeda
Maintainer
Julia Fukuyama
Last Published
May 14th, 2021
Functions in treeDA (0.0.5)
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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