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This function plots the feature ranking results from a fitted 'RaSE'
object via ggplot2
. In the figure, x-axis represents the feature number and y-axis represents the selected percentage of each feature in B1 subspaces.
RaPlot(
object,
main = NULL,
xlab = "feature",
ylab = "selected percentage",
...
)
fitted 'RaSE'
model object.
title of the plot. Default = NULL
, which makes the title following the orm 'RaSE-base' with subscript i (rounds of iterations), where base represents the type of base classifier. i is omitted when it is zero.
the label of x-axis. Default = 'feature'.
the label of y-axis. Default = 'selected percentage'.
additional arguments.
a 'ggplot'
object.
Tian, Y. and Feng, Y., 2021. RaSE: Random subspace ensemble classification. Journal of Machine Learning Research, 22(45), pp.1-93.
Rase
.
# NOT RUN {
set.seed(0, kind = "L'Ecuyer-CMRG")
train.data <- RaModel("classification", 1, n = 100, p = 50)
xtrain <- train.data$x
ytrain <- train.data$y
# fit RaSE classifier with QDA base classifier
fit <- Rase(xtrain, ytrain, B1 = 50, B2 = 50, iteration = 1, base = 'qda',
cores = 2, criterion = 'ric')
# plot the selected percentage of each feature appearing in B1 subspaces
RaPlot(fit)
# }
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