show-methods: Show description of a Rmixmod class to standard output.

In Rmixmod: Classification with Mixture Modelling

Show description of a Rmixmod class to standard output.

Description

Show description of a Rmixmod class to standard output.

Usage

## S4 method for signature 'Model'
show(object)

## S4 method for signature 'MultinomialParameter'
show(object)

## S4 method for signature 'GaussianParameter'
show(object)

## S4 method for signature 'CompositeParameter'
show(object)

## S4 method for signature 'MixmodResults'
show(object)

## S4 method for signature 'Mixmod'
show(object)

## S4 method for signature 'Strategy'
show(object)

## S4 method for signature 'MixmodCluster'
show(object)

## S4 method for signature 'MixmodDAResults'
show(object)

## S4 method for signature 'MixmodLearn'
show(object)

## S4 method for signature 'MixmodPredict'
show(object)

Arguments

object

a Rmixmod object: a Strategy, a Model, a GaussianParameter, a MultinomialParameter, a MixmodResults, a MixmodCluster, a MixmodLearn or a MixmodPredict.

Value

NULL. Prints to standard out.

See Also

show

Examples

## for strategy
strategy <- mixmodStrategy()
show(strategy)

## for Gaussian models
gmodel <- mixmodGaussianModel()
show(gmodel)
## for multinomial models
mmodel <- mixmodMultinomialModel()
show(mmodel)

## for clustering
data(geyser)
xem <- mixmodCluster(geyser, 3)
show(xem)
## for Gaussian parameters
show(xem["bestResult"]["parameters"])

## for discriminant analysis
# start by extract 10 observations from iris data set
iris.partition <- sample(1:nrow(iris), 10)
# then run a mixmodLearn() analysis without those 10 observations
learn <- mixmodLearn(iris[-iris.partition, 1:4], iris$Species[-iris.partition])
# create a MixmodPredict to predict those 10 observations
prediction <- mixmodPredict(
  data = iris[iris.partition, 1:4],
  classificationRule = learn["bestResult"]
)
# show results
show(prediction)

Rmixmod documentation built on May 29, 2024, 7:32 a.m.