randomForest {MetNet} | R Documentation |
randomForest
infers an adjacency matrix using
random forest using the rfPermute
function from the
rfPermute
package. randomForest
extracts the p-values
by the function rp.importance
and writes the presence/absence based
on the significance value (α ≤q 0.05) of this
connection to a matrix. The adjacency matrix is returned.
randomForest(x, parallel=FALSE, randomForest_adjust="none", ...)
x |
matrix, where columns are the samples and the rows are features (metabolites), cell entries are intensity values |
parallel |
logical, should computation be parallelized? If
|
randomForest_adjust |
character, correction method for p-values from
|
... |
parameters passed to |
For use of the parameters used in the rfPermute
function,
refer to ?rfPermute::rfPermute.default.
matrix, matrix with edges inferred from random forest algorithm
rfPermute
and rp.importance
Thomas Naake, thomasnaake@googlemail.com
data("x_test", package="MetNet") x <- x_test[, 3:dim(x_test)[2]] x <- as.matrix(x) ## Not run: randomForest(x)