trainWrapper

wrapper

<code>data.frame</code> of the train dataset without the class column

train

a vector containing the class column for <code>train</code>

trainClass

further arguments for <code>wrapper</code>

Generic methods to train classifiers

Class imbalance usually damages the performance of classifiers. Thus, it is
important to treat data before applying a classifier algorithm. This package
includes recent resampling algorithms in the literature: (Barua et al. 2014)
<doi:10.1109/tkde.2012.232>; (Das et al. 2015) <doi:10.1109/tkde.2014.2324567>,
(Zhang et al. 2014) <doi:10.1016/j.inffus.2013.12.003>; (Gao et al. 2014)
<doi:10.1016/j.neucom.2014.02.006>; (Almogahed et al. 2014)
<doi:10.1007/s00500-014-1484-5>. It also includes an useful interface to
perform oversampling.

Last chance! 50% off unlimited learning

trainWrapper: Generic methods to train classifiers

Description

Usage

Arguments

Value

See Also

Examples