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summary.classif

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 manuel.oviedo@usc.es

See Also

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

Functional Data Analysis and Utilities for Statistical Computing

v2.0.2
GPL-2
Authors
Manuel Febrero Bande [aut], Manuel Oviedo de la Fuente [aut, cre], Pedro Galeano [ctb], Alicia Nieto [ctb], Eduardo Garcia-Portugues [ctb]
Initial release
2020-02-17

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