validateModel,ClinicalModel,CohortList-method {PDATK} | R Documentation

## Evaluate the Performance of a List of Trained KTSP Models from a PCOSP Model

### Description

Evaluate the Performance of a List of Trained KTSP Models from a PCOSP Model

### Usage

    ## S4 method for signature 'ClinicalModel,CohortList'
    validateModel(model, valData, ...)

### Arguments

`model` | A trained `ClinicalModel` object, as returned by the `trainModel` method.
`valData` | A `CohortList` containing one or more `SurvivalExperiment`s. The first assay in each `SurvivalExperiment` will be classified using all top scoring KTSP models in `models(model)`.
`...` | Fallthrough arguments to `BiocParallel::bplapply`, use this to configure the parallelization settings for this function. For example to specify BPARAM.

### Value

The `model` object with the validationStats and validationData slots occupied.

### See Also

`BiocParallel::bplapply`, `switchBox::SWAP.KTSP.Classify`

### Examples

    data(sampleClinicalModel)
    data(samplePCSIsurvExp)

    # Set parallelization settings
    BiocParallel::register(BiocParallel::SerialParam())

    # Train Model
    trainedClinicalModel <- trainModel(sampleClinicalModel)

    # Make predictions
    clinicalPredSurvExp <- predictClasses(samplePCSIsurvExp,
      model=trainedClinicalModel)

    # Validate model
    validatedClincalModel <- validateModel(trainedClinicalModel,
      valData=clinicalPredSurvExp)

[Package PDATK version 1.0.2 Index]