SOMB {MLInterfaces} | R Documentation

## An interface to self-organizing map methods for ExpressionSets

### Description

Self-organizing maps are covered in various machine learning reviews. These can be viewed as clustering procedures analogous to `kmeans` but with a constraint on the complexity of the subspace in which the cluster-defining prototypes are identified.

The outputs of `som` and `SOM` are not easily formulated as `clustOutput-class` instances, so classes that extend `list` are used as output containers.

SOMB(exprObj, classifLab) somB(exprObj, classifLab)

### Arguments

`exprObj` | An instance of the `ExpressionSet` class.
`classifLab` | A vector of class labels.

### Details

You may pass additional parameters, see `SOM` or `som` for details.

### Value

An object of class `SOMBoutput` or `somBoutput`

### Author(s)

Jess Mar, VJ Carey <stvjc@channing.harvard.edu>

### Examples

    # access and trim an ExpressionSet
    library(golubEsets)
    data(Golub_Merge)
    smallG <- Golub_Merge[1:60,]
    # set a PRNG seed for reproducibilitiy
    set.seed(1234) # needed for nnet initialization
    # now run the classifiers
    #somB( smallG, "ALL.AML", 3)
    SOMB( smallG, "ALL.AML", 3)

[Package MLInterfaces version 1.12.0 Index]