RMOA (version 1.1.0)

MOA_classification_ensemblelearning: MOA classification using ensembles

Description

MOA classification using ensembles (bagging/boosting/stacking/other)

Usage

AccuracyUpdatedEnsemble(control = NULL, ...)
AccuracyWeightedEnsemble(control = NULL, ...)
ADACC(control = NULL, ...)
DACC(control = NULL, ...)
LeveragingBag(control = NULL, ...)
LimAttClassifier(control = NULL, ...)
OCBoost(control = NULL, ...)
OnlineAccuracyUpdatedEnsemble(control = NULL, ...)
OzaBag(control = NULL, ...)
OzaBagAdwin(control = NULL, ...)
OzaBagASHT(control = NULL, ...)
OzaBoost(control = NULL, ...)
OzaBoostAdwin(control = NULL, ...)
TemporallyAugmentedClassifier(control = NULL, ...)
WeightedMajorityAlgorithm(control = NULL, ...)

Value

An object of class MOA_classifier which sets up an untrained MOA model, which can be trained using trainMOA

Arguments

control

an object of class MOAmodelOptions as obtained by calling MOAoptions

...

options of parameters passed on to MOAoptions, in case control is left to NULL. Ignored if control is supplied

See Also

MOAoptions, trainMOA

Examples

ctrl <- MOAoptions(model = "OzaBoostAdwin")
mymodel <- OzaBoostAdwin(control=ctrl)
mymodel