predictClasses,ConsensusMetaclusteringModel,ANY-method {PDATK} | R Documentation

## Compute the Optimal Clustering Solution for a Trained ConsensusMetaclusteringModel

### Description

Compute the optimal clustering solution out of possibilities generated with trainModel. Assigns the cluster labels to the `MultiAssayExperiment` object.

### Usage

    ## S4 method for signature 'ConsensusMetaclusteringModel,ANY'
    predictClasses(object, ..., optimal_k_function = optimalKMinimizeAmbiguity)

### Arguments

`object` | A `MutliAssayExperiment` object
`...` | Fall through arguments to `optimal_k_function`. For the default `optimal_k_function`, you can specify `subinterval` argument which defines the interval of the ECDF to minimize ambiguity over. Defaults to `c(0.1, 0.9)` if not specified. See `?optimalKMinimizeAmbiguity` for more details on the `subinterval` parameter.
`optimal_k_function` | A function which accepts as its input `models(object)` of a trained `ConsensusMetaclusteringModel` object, and returns a vector of optimal K values, one for each assay in `rawdata(object)`. The default method is `optimalKMinimizeAmbiguity`, see `?optimalKMinimizeAmbiguity` for more details. Please note this argument must be named or it will not work.

### Value

A `object` `ConsensusMetaclusteringModel`, with class predictions assigned to the colData of `trianData`

[Package PDATK version 1.2.0 Index]