R: testFilters

testFilters {TSEAL}

R Documentation

testFilters

Description

This function performs a test with a series of filters defined by the user, for the maximum number of variables determined. This function can be used to compare the performance of different filters with a different number of variables to be considered and the differences between a linear and a quadratic discriminant.

Usage

testFilters(
  series,
  labels,
  maxvars,
  filters = c("haar", "d4", "d6", "d8", "la8"),
  features = c("Var", "Cor", "IQR", "PE", "DM"),
  lev = 0
)

Arguments

`series`	Samples from the population (dim x length x cases)
`labels`	Labeled vector that classify the observations.
`maxvars`	maximum number of variables included by the StepDiscrim algorithm. Must be grater than 0 and, in normal cases, lesser than 100
`filters`	Vector indicating the filters to be tested. To see the available filters use the function `availableFilters`
`features`	A list of characteristics that will be used for the classification process. To see the available features see `availableFeatures`
`lev`	Wavelet decomposition level, by default is selected using the "conservative" strategy. See `chooseLevel` function.

Value

A list that each element contains:

CM: confusion matrix with a particular configuration using LOOCV
Classification: a vector with the raw classification result. "1" if the observation belongs to the population 1 and "2" if belongs to the population 2.
NVars: the total numbers of variables have been taken into account in the classification process
Method: type of classifier used.
Filter: filter used in the MultiWave analysis process
Features: vector containing the features taken into account

Examples


load(system.file("extdata/ECGExample.rda",package = "TSEAL"))
# The dataset has the first 5 elements of class 1
# and the last 5 of class 2.
labels <- c(rep(1, 5), rep(2, 5))
result <- testFilters(ECGExample, labels, features=c("var","cor"),
          filters= c("haar","d4"), maxvars = 3)