fda.usc (version 1.5.0)

summary.classif: Summarizes information from kernel classification methods.

Description

Summary function for classif.knn or classif.kernel.

Usage

# S3 method for classif
summary(object,…)
# S3 method for classif
print(x,digits = max(3, getOption("digits") - 3),…)

Arguments

object

Estimated by kernel classification.

x

Estimated by kernel classification.

digits

a non-null value for digits specifies the minimum number of significant digits to be printed in values. The default, NULL, uses getOption(digits).

…

Further arguments passed to or from other methods.

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).

object

Estimated by kernel classification.

Details

object from one of the following functions:

	classif.knn
	classif.kernel

See Also

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

Examples

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

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