MLearn-methods {pRoloc} | R Documentation

## The `MLearn` interface for machine learning

### Description

This method implements `MLInterfaces`' `MLean` method for instances of the class `"MSnSet"`.

### Methods

`signature(formula = "formula", data = "MSnSet", .method = "learnerSchema", trainInd = "numeric")`

  The learning problem is stated with the `formula` and applies the `.method` schema on the `MSnSet` `data` input using the `trainInd` numeric indices as train data.

`signature(formula = "formula", data = "MSnSet", .method = "learnerSchema", trainInd = "xvalSpec")`

  In this case, an instance of `xvalSpec` is used for cross-validation.

`signature(formula = "formula", data = "MSnSet", .method = "clusteringSchema", trainInd = "missing")`

  Hierarchical (`hclustI`), k-means (`kmeansI`) and partitioning around medoids (`pamI`) clustering algorithms using `MLInterface`'s `MLearn` interface.

### See Also

The `MLInterfaces` package documentation, in particular `MLearn`.

[Package pRoloc version 1.26.0 Index]