Description Usage Arguments Value References Examples
Plot principle components of the proximity matrix
1 2 3 |
pca |
a prcomp object, pca of an n x n matrix giving the proportion of times across all trees that observation i,j are in the same terminal node |
dims |
integer vector of length 2 giving indices for the dimensions of |
labels |
length n character vector giving observation labels |
alpha |
optional continuous vector of length n make points/labels transparent or a numeric of length 1 giving the alpha of all points/labels |
alpha_label |
character legend title if alpha parameter used |
color |
optional discrete vector of length n which colors the points/labels or a character vector giving the color of all points/labels |
color_label |
character legend title if color parameter is used |
shape |
optional discrete vector of length n which shapes points (not applicable if labels used) or a character vector of length 1 which gives the shape of all points |
shape_label |
character legend title if shape parameter is used |
size |
optional continuous vector of length n which sizes points or labels or a numeric of length 1 which gives the sizes of all the points |
size_label |
character legend title if size parameter used |
xlab |
character x-axis label |
ylab |
character y-axis label |
title |
character plot title |
a ggplot object
https://github.com/vqv/ggbiplot
Gabriel, "The biplot graphic display of matrices with application to principal component analysis," Biometrika, 1971
1 2 3 4 5 6 7 8 9 10 11 | library(randomForest)
fit = randomForest(hp ~ ., mtcars, proximity = TRUE)
prox = extract_proximity(fit)
pca = prcomp(prox, scale = TRUE)
plot_prox(pca, labels = row.names(mtcars))
fit = randomForest(Species ~ ., iris, proximity = TRUE)
prox = extract_proximity(fit)
pca = prcomp(prox, scale = TRUE)
plot_prox(pca, color = iris$Species, color_label = "Species", size = 2)
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randomForest 4.6-14
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