addNoisyCopies: Add noisy copies for parametric bootstrap

Description Usage Arguments Value References

View source: R/sfaParamBoot.R

Description

Given training data X with true labels REALCLASS, add new records to X and REALCLASS, which are noisy copies of the training data.

Usage

1
addNoisyCopies(realclass, x, pars)

Arguments

x

a matrix containing the training data

realclass

true class of training data (can be vector, numerics, integers, factors)

pars

list of parameters:
pars$ncopies: Number of new records to add
pars$ncsort: Defines if training data should be sorted by class. Default is FALSE
pars$ncsigma: The noise in each column of x has the std.dev. pars$ncsigma*(standard deviation of column). Default Value: 0.8
pars$ncmethod: =1: each 'old' record from X in turn is the centroid for a new pattern;
=2: the centroid is the average of all records from the same class, the std.dev. is the same for all classes;
=3: centroid as in '2', the std.dev. is the std.dev. of all records from the same class (*recommended*)

Value

list res
- res contains two list entries: realclass and x (including added copies)

References

sfaPBootstrap


rSFA documentation built on May 30, 2017, 6:48 a.m.