trainModel,RGAModel-method {PDATK} | R Documentation |
Uses the switchBox SWAP.Train.KTSP function to fit a number of k top scoring pair models to the data, filtering the results to the best models based on the specified paramters.
## S4 method for signature 'RGAModel' trainModel(object, numModels = 10, minAccuracy = 0, ...)
object |
A |
numModels |
An |
minAccuracy |
A |
... |
Fall through arguments to |
This function is parallelized with BiocParallel, thus if you wish to change the back-end for parallelization, number of threads, or any other parallelization configuration please pass BPPARAM to bplapply.
A RGAModel
object with the trained model in the model
slot.
switchBox::SWAP.KTSP.Train
BiocParallel::bplapply
data(sampleRGAmodel) set.seed(getModelSeed(sampleRGAmodel)) # Set parallelization settings BiocParallel::register(BiocParallel::SerialParam()) trainedRGAmodel <- trainModel(sampleRGAmodel, numModels=2, minAccuracy=0)