TSEAL (version 0.1.3)

testFilters: 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
)

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

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.

See Also

• LOOCV

• MultiWaveAnalysis

• StepDiscrim

• availableFilters

• availableFeatures

Examples

# \donttest{
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)
# }