normalize {sparseLDA} | R Documentation |
Normalize a vector or matrix to zero mean and unit length columns
normalize(X)
X |
a matrix with the training data with observations down the rows and variables in the columns. |
The function can e.g. be used for the training data in sda or smda.
Returns a list with the following attributes:
Xc |
The normalized data. |
mx |
Mean of columns of X. |
vx |
Length of columns of X. |
Id |
Logical vector indicating which variables are included in X. If some of the columns have zero length they are omitted. |
Line Clemmensen
Clemmensen, L., Hastie, T. and Ersboell, K. (2008) "Sparse discriminant analysis", Technical report, IMM, Technical University of Denmark
## Data X<-matrix(sample(seq(3),12,replace=TRUE),nrow=3) ## Normalize data Nm<-normalize(X) print(Nm$Xc) ## See if any variables have been removed which(!Nm$Id)