Description Usage Arguments Value Methods References Examples
Grow more trees in a random forest, using the same parameters.
1 2 3 |
forest |
A random forest of class |
x |
A |
ntrees |
The number of additional trees to grow in the forest. Default: 50. |
printerrfreq |
An integer, specifying how often error estimates should be printed to the screen. Default: error estimates will be printed every 10 trees. |
printclserr |
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reuse.cache |
|
trace |
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The object supplied as the forest
argument, with additional trees grown.
signature(forest = "bigcforest")
Grow more trees in a classification random forest.
Breiman, L. (2001). Random forests. Machine learning, 45(1), 5-32.
Breiman, L. & Cutler, A. (n.d.). Random Forests. Retrieved from http://www.stat.berkeley.edu/~breiman/RandomForests/cc_home.htm.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | # Classify cars in the Cars93 data set by type (Compact, Large,
# Midsize, Small, Sporty, or Van).
# Load data.
data(Cars93, package="MASS")
x <- Cars93
y <- Cars93$Type
# Select variables with which to train model.
vars <- c(4:22)
# Run model, grow 30 trees.
forest <- bigrfc(x, y, ntree=30L, varselect=vars, cachepath=NULL)
# Grow 10 more trees.
forest <- grow(forest, x, ntree=10L)
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