evaluateParameters {macat} | R Documentation |
For a given data set, chromosome, class, and kernel function, this function helps in determining optimal settings for the kernel parameter(s). The performance of individual parameter setting is assessed by cross- validation.
evaluateParameters(data, class, chromosome, kernel, kernelparams = NULL, paramMultipliers = 2^(-4:4), subset = NULL, newlabels = NULL, ncross = 10, verbose = TRUE)
data |
Gene expression data in the MACAT list format. See data(stjude) for an example. |
class |
Sample class to be analyzed |
chromosome |
Chromosome to be analyzed |
kernel |
Choose kernel to smooth scores along the chromosome. Available are 'kNN' for k-Nearest-Neighbors, 'rbf' for radial-basis-function (Gaussian), 'basePairDistance' for a kernel, which averages over all genes within a given range of base pairs around a position. |
kernelparams |
Additional parameters for the kernel as list, e.g., kernelparams=list(k=5) for taking the 5 nearest neighbours in the kNN-kernel. If NULL some defaults are set within the function. |
paramMultipliers |
Numeric vector. If you do cross-validation of the kernel parameters, specify these as multipliers of the given (standard) kernel parameter, depending on your kernel choice (see page 5 of the vignette). The multiplication results are the kernel argument settings, among which you want to search for the optimal one using cross-validation. |
subset |
If a subset of samples is to be used, give vector of column- indices of these samples in the original matrix here. |
newlabels |
If other labels than the ones in the MACAT-list-structure are to be used, give them as character vector/factor here. Make sure argument 'class' is one of them. |
ncross |
Integer. Specify how many folds in cross-validation. |
verbose |
Logical. Should progress be reported to STDOUT? |
A list of class 'MACATevP' with 4 components:
[parameterName] |
List of assessed settings for the parameter [parameterName]. |
avgResid |
Average Residual Sum of Squares for the parameter settings in the same order as the first component. |
multiplier |
Multiplier of the original parameters in the same order as the first components. |
best |
List of parameter settings considered optimal by cross- validation. Can be directly inserted under the argument 'kernelparams' of the 'evalScoring' function. |
MACAT development team
data(stjd) evalkNN6 <- evaluateParameters(stjd, class="T", chromosome=6,kernel=kNN, paramMultipliers=c(0.01,seq(0.2,2.0,0.2),2.5)) if (interactive()&&capabilities("X11")) plot(evalkNN6)