trainMOA.MOA_classifier {RMOA} | R Documentation |
Train a MOA classifier (e.g. a HoeffdingTree) on a datastream
Description
Train a MOA classifier (e.g. a HoeffdingTree) on a datastream
Usage
## S3 method for class 'MOA_classifier'
trainMOA(model, formula, data, subset,
na.action = na.exclude, transFUN = identity, chunksize = 1000,
reset = TRUE, trace = FALSE, options = list(maxruntime = +Inf), ...)
Arguments
model |
an object of class |
formula |
a symbolic description of the model to be fit. |
data |
an object of class |
subset |
an optional vector specifying a subset of observations to be used in the fitting process. |
na.action |
a function which indicates what should happen when the data contain |
transFUN |
a function which is used after obtaining |
chunksize |
the number of rows to obtain from the |
reset |
logical indicating to reset the |
trace |
logical, indicating to show information on how many datastream chunks are already processed
as a |
options |
a names list of further options. Currently not used. |
... |
other arguments, currently not used yet |
Value
An object of class MOA_trainedmodel which is a list with elements
model: the updated supplied
model
object of classMOA_classifier
call: the matched call
na.action: the value of na.action
terms: the
terms
in the modeltransFUN: the transFUN argument
See Also
MOA_classifier
, datastream_file
, datastream_dataframe
,
datastream_matrix
, datastream_ffdf
, datastream
,
predict.MOA_trainedmodel
Examples
hdt <- HoeffdingTree(numericEstimator = "GaussianNumericAttributeClassObserver")
hdt
data(iris)
iris <- factorise(iris)
irisdatastream <- datastream_dataframe(data=iris)
irisdatastream$get_points(3)
mymodel <- trainMOA(model = hdt, Species ~ Sepal.Length + Sepal.Width + Petal.Length,
data = irisdatastream, chunksize = 10)
mymodel$model
irisdatastream$reset()
mymodel <- trainMOA(model = hdt,
Species ~ Sepal.Length + Sepal.Width + Petal.Length + Petal.Length^2,
data = irisdatastream, chunksize = 10, reset=TRUE, trace=TRUE)
mymodel$model