ddalpha (version 1.3.16)

compclassf.classify: Classify using Functional Componentwise Classifier

Description

Classifies data using the functional componentwise classifier.

Usage

compclassf.classify(compclassf, objectsf, subset, ...)
# S3 method for compclassf
predict(object, objectsf, subset, ...)

Value

List containing class labels.

Arguments

compclassf, object

Functional componentwise classifier (obtained by compclassf.train).

objectsf

list containing lists (functions) of two vectors of equal length, named "args" and "vals": arguments sorted in ascending order and corresponding them values respectively

subset

an optional vector specifying a subset of observations to be classified.

...

additional parameters, passed to the classifier, selected with parameter classifier.type in compclassf.train.

References

Delaigle, A., Hall, P., and Bathia, N. (2012). Componentwise classification and clustering of functional data. Biometrika 99 299--313.

See Also

compclassf.train to train the functional componentwise classifier.

Examples

if (FALSE) {
## load the Growth dataset
dataf = dataf.growth()

learn = c(head(dataf$dataf, 49), tail(dataf$dataf, 34))
labels =c(head(dataf$labels, 49), tail(dataf$labels, 34)) 
test = tail(head(dataf$dataf, 59), 10)    # elements 50:59. 5 girls, 5 boys

c = compclassf.train (learn, labels, classifier.type = "ddalpha")

classified = compclassf.classify(c, test)

print(unlist(classified))

}