penaltyLearning (version 2020.5.13)

featureVector: featureVector

Description

Compute a feature vector of constant length which can be used as an input for supervised penalty learning. The output is a target interval of log(penalty) values that achieve minimum incorrect labels (see targetIntervals).

Usage

featureVector(data.vec)

Arguments

data.vec

numeric vector of ordered data.

Value

Numeric vector of features.

Examples

# NOT RUN {
x <- rnorm(10)
penaltyLearning::featureVector(x)
if(requireNamespace("neuroblastoma")){
  data(neuroblastoma, package="neuroblastoma", envir=environment())
  one <- subset(neuroblastoma$profiles, profile.id=="1" & chromosome=="1")
  (f.vec <- penaltyLearning::featureVector(one$logratio))
}

# }