ddalpha (version 1.3.16)

ddalphaf.test: Test Functional DD-Classifier

Description

Trains functional DD-classifier on the learning sequence of the data and tests it on the testing sequence.

Usage

ddalphaf.test(learn, learnlabels, test, testlabels, disc.type = c("LS", "comp"), ...)

Value

error

the part of incorrectly classified data

correct

the number of correctly classified objects

incorrect

the number of incorrectly classified objects

total

the number of classified objects

ignored

the number of ignored objects (outside the convex hull of the learning data)

n

the number of objects in the testing sequence

time

training time

Arguments

learn

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

learnlabels

list of output labels of the functional observations

test

the testing sequence. Has the same format as learn

disc.type

type of the used discretization scheme. "LS" for ddalphaf.train, "comp" for for compclassf.train

testlabels

list of output labels of the functinal observations

...

additional parameters passed to ddalphaf.train

See Also

ddalphaf.train to train the functional DD\(\alpha\)-classifier, ddalphaf.classify for classification using functonal DD\(\alpha\)-classifier, ddalphaf.getErrorRateCV and ddalphaf.getErrorRatePart to get error rate of the functional DD-classifier on particular data.

Examples

# load the fdata
df = dataf.growth()

samp = c(35:70)

ddalphaf.test(learn = df$dataf[-samp], learnlabels = df$labels[-samp], 
              test =  df$dataf[samp],  testlabels =  df$labels[samp], 
              adc.args = list(instance = "avr", 
                              numFcn = 2, 
                              numDer = 2))