rotationForest {rotationForest} | R Documentation |
rotationForest
implements an ensemble method where each base classifier (tree) is fit on the principal components of the variables of random partitions of the feature set.
rotationForest(x, y, K = round(ncol(x)/3, 0), L = 10, verbose = FALSE,
...)
x |
A data frame of predictors (numeric, or integer). Categorical variables need to be transformed to indicator (dummy) variables. At minimum |
y |
A factor containing the response vector. Only {0,1} is allowed. |
K |
The number of variable subsets. The default is the value |
L |
The number of base classifiers (trees using the |
verbose |
Boolean. Should information about the subsets be printed? |
... |
Arguments to |
An object of class rotationForest
, which is a list with the following elements:
models |
A list of trees. |
loadings |
A list of loadings. |
columnnames |
Column names of x. |
Michel Ballings and Dirk Van den Poel, Maintainer: Michel.Ballings@GMail.com
Rodriguez, J.J., Kuncheva, L.I., 2006. Rotation forest: A new classifier ensemble method. IEEE Trans. Pattern Anal. Mach. Intell. 28, 1619-1630. doi:10.1109/TPAMI.2006.211
data(iris)
y <- as.factor(ifelse(iris$Species[1:100]=="setosa",0,1))
x <- iris[1:100,-5]
rF <- rotationForest(x,y)
predict(object=rF,newdata=x)