summary.classif: Summarizes information from kernel classification methods.

In fda.usc: Functional Data Analysis and Utilities for Statistical Computing

Summarizes information from kernel classification methods.

Description

Summary function for classif.knn or classif.kernel.

Usage

## S3 method for class 'classif'
summary(object, ...)

## S3 method for class 'classif'
print(x, digits = max(3, getOption("digits") - 3), ...)

Arguments

object	Estimated by kernel classification.
...	Further arguments passed to or from other methods.
x	Estimated by kernel classification.
digits	how many significant digits are to be used for numeric and complex x.

Details

object from classif.knn or classif.kernel

Value

Shows:

• -Probability of correct classification by group prob.classification.

• -Confusion matrix between the theoretical groups and estimated groups.

• -Highest probability of correct classification max.prob.

If the object is returned from the function classif.knn

• -Vector of probability of correct classification by number of neighbors knn.

• -Optimal number of neighbors: knn.opt.

If the object is returned from the function: classif.kernel

• -Vector of probability of correct classification by banwidth h.

• -Functional measure of closeness (optimal distance, h.opt).

Author(s)

Manuel Febrero-Bande, Manuel Oviedo de la Fuente [e-mail]

See Also

See Also as: classif.knn, classif.kernel
and summary.classif

Examples

## Not run:  
data(phoneme)
mlearn<-phoneme[["learn"]]
glearn<-phoneme[["classlearn"]]
out=classif.knn(glearn,mlearn,knn=c(3,5,7))
summary(out)
out2=classif.kernel(glearn,mlearn,h=2^(0:5))
summary(out2)

## End(Not run)

fda.usc documentation built on Oct. 17, 2022, 9:06 a.m.