addNoisyCopies {rSFA} | R Documentation |
Add noisy copies for parametric bootstrap
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
addNoisyCopies(realclass, x, pars)
Arguments
realclass |
true class of training data (can be vector, numerics, integers, factors)
|
x |
a matrix containing the training data
|
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
[Package
rSFA version 1.5
Index]