Available-classifiers {MLSeq} | R Documentation

## Available classification/regression methods in `MLSeq`

### Description

This function returns a character vector of available classification/regression methods in `MLSeq`. These methods are imported from `caret` package. See details below.

### Usage

    availableMethods(model = NULL, regex = TRUE, ...)

    printAvailableMethods()

### Arguments

`model` | a character string indicating the name of classification model. If NULL, all the available methods from `MLSeq` is returned. Otherwise, the methods which are complete or partial matches to requested string is returned. See `regex` for details.
`regex` | a logical: should a regular expressions be used? If FALSE, a simple match is conducted against the whole name of the model.
`...` | options to pass to `grepl`.

### Details

There are 200+ methods available in `caret`. We import approximately 85 methods which are available for "classification" task. Some of these methods are available for both classification and regression tasks. `availableMethods()` returns a character vector of available methods in `MLSeq`. These names are directly used in `classify` function with arguement `method`. See http://topepo.github.io/caret/available-models.html for a complete list of available methods in `caret`. Run `printAvailableMethods()` to print detailed information about classification methods (prints to R Console).

### Value

a requested or complete character vector of available methods.

### Note

Available methods in `MLSeq` will be regularly updated. Some of the methods might be removed as well as some others took its place in `MLSeq`. Please check the available methods before fitting the model. This function is inspired from the function `getModelInfo()` in `caret` and some of the code chunks and help texts are used here.

### See Also

`classify`, `getModelInfo`, `train`

[Package MLSeq version 2.6.0 Index]