Available-classifiers: Available classification/regression methods in 'MLSeq'

In dncR/MLSeq: Machine Learning Interface for RNA-Seq Data

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

dncR/MLSeq documentation built on May 17, 2020, 6:45 p.m.