Synthesis with random forest
Generates univariate synthetic data using Breiman's random forest algorithm
classification and regression. It uses randomForest
function
from the randomForest package.
syn.rf(y, x, xp, smoothing = "", proper = FALSE, ntree = 10, ...)
y |
an original data vector of length |
x |
a matrix ( |
xp |
a matrix ( |
smoothing |
smoothing method for continuous variables. |
proper |
... |
ntree |
number of trees to grow. |
... |
additional parameters passed to
|
...
A list with two components:
res |
a vector of length |
fit |
the fitted model which is an object of class |
...
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