compclassf.classify: Classify using Functional Componentwise Classifier

In ddalpha: Depth-Based Classification and Calculation of Data Depth

Classify using Functional Componentwise Classifier

Description

Classifies data using the functional componentwise classifier.

Usage

compclassf.classify(compclassf, objectsf, subset, ...)

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

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.

Value

List containing class labels.

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

## Not run: 
## 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))


## End(Not run)

ddalpha documentation built on March 23, 2022, 9:07 a.m.