1% Generated by roxygen2: do not edit by hand
2% Please edit documentation in R/fastica.R
3\docType{class}
4\name{FastICA-class}
5\alias{FastICA-class}
6\alias{FastICA}
7\title{Independent Component Analysis}
8\description{
9An S4 Class implementing the FastICA algorithm for Indepentend
10Component Analysis.
11}
12\details{
13ICA is used for blind signal separation of different sources. It is
14a linear Projection.
15}
16\section{Slots}{
17
18\describe{
19\item{\code{fun}}{A function that does the embedding and returns a
20dimRedResult object.}
21
22\item{\code{stdpars}}{The standard parameters for the function.}
23}}
24
25\section{General usage}{
26
27Dimensionality reduction methods are S4 Classes that either be used
28directly, in which case they have to be initialized and a full
29list with parameters has to be handed to the \code{@fun()}
30slot, or the method name be passed to the embed function and
31parameters can be given to the \code{...}, in which case
32missing parameters will be replaced by the ones in the
33\code{@stdpars}.
34}
35
36\section{Parameters}{
37
38FastICA can take the following parameters:
39\describe{
40  \item{ndim}{The number of output dimensions. Defaults to \code{2}}
41}
42}
43
44\section{Implementation}{
45
46Wraps around \code{\link[fastICA]{fastICA}}. FastICA uses a very
47fast approximation for negentropy to estimate statistical
48independences between signals. Because it is a simple
49rotation/projection, forward and backward functions can be given.
50}
51
52\examples{
53dat <- loadDataSet("3D S Curve")
54emb <- embed(dat, "FastICA", ndim = 2)
55plot(getData(getDimRedData(emb)))
56
57}
58\references{
59Hyvarinen, A., 1999. Fast and robust fixed-point algorithms for independent
60component analysis. IEEE Transactions on Neural Networks 10, 626-634.
61https://doi.org/10.1109/72.761722
62}
63\seealso{
64Other dimensionality reduction methods:
65\code{\link{AutoEncoder-class}},
66\code{\link{DRR-class}},
67\code{\link{DiffusionMaps-class}},
68\code{\link{DrL-class}},
69\code{\link{FruchtermanReingold-class}},
70\code{\link{HLLE-class}},
71\code{\link{Isomap-class}},
72\code{\link{KamadaKawai-class}},
73\code{\link{LLE-class}},
74\code{\link{MDS-class}},
75\code{\link{NNMF-class}},
76\code{\link{PCA-class}},
77\code{\link{PCA_L1-class}},
78\code{\link{UMAP-class}},
79\code{\link{dimRedMethod-class}},
80\code{\link{dimRedMethodList}()},
81\code{\link{kPCA-class}},
82\code{\link{nMDS-class}},
83\code{\link{tSNE-class}}
84}
85\concept{dimensionality reduction methods}
86