Usage
perTurboOptimisation(object, fcol = "markers", pRegul = 10^(seq(from = -1, to = 0, by = 0.2)), sigma = 10^(seq(from = -1, to = 1, by = 0.5)), inv = c("Inversion Cholesky", "Moore Penrose", "solve", "svd"), reg = c("tikhonov", "none", "trunc"), times = 1, test.size = 0.2, xval = 5, fun = mean, seed, verbose = TRUE)
Arguments
object
An instance of class "MSnSet".
fcol
The feature meta-data containing marker definitions.
Default is markers.
pRegul
The hyper-parameter for the regularisation (values are in ]0,1] ).
If reg =="trunc", pRegul is for the percentage of eigen values in matrix.
If reg =="tikhonov", then 'pRegul' is the parameter for the tikhonov regularisation.
Available configurations are :
"Inversion Cholesky" - ("tikhonov" / "none"),
"Moore Penrose" - ("tikhonov" / "none"),
"solve" - ("tikhonov" / "none"),
"svd" - ("tikhonov" / "none" / "trunc").
sigma
The hyper-parameter.
inv
The type of algorithm used to invert the matrix.
Values are :
"Inversion Cholesky" (chol2inv),
"Moore Penrose" (ginv),
"solve" (solve),
"svd" (svd).
Default value is "Inversion Cholesky". reg
The type of regularisation of matrix.
Values are "none", "trunc" or "tikhonov".
Default value is "tikhonov".
times
The number of times internal cross-validation is performed.
Default is 100.
test.size
The size of test data. Default is 0.2 (20 percent).
xval
The n-cross validation. Default is 5.
fun
The function used to summarise the times macro F1 matrices.
seed
The optional random number generator seed.
verbose
A logical defining whether a progress bar is displayed.