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.