sfaClassify: Predict Class for SFA classification

In rSFA: Slow Feature Analysis

Predict Class for SFA classification

Description

Create a SFA classification mode, predict & evaluate on new data (xtst,realc_tst).
Author of orig. matlab version: Wolfgang Konen, May 2009 - Jan 2010
See also [Berkes05] Pietro Berkes: Pattern recognition with Slow Feature Analysis. Cognitive Sciences EPrint Archive (CogPrint) 4104, http://cogprints.org/4104/ (2005)

Usage

sfaClassify(x, realclass, xtst = 0, realcTst = 0, opts)

Arguments

x	NREC x IDIM, training input data
realclass	1 x NREC, training class labels
xtst	NTST x IDIM, test input data
realcTst	1 x NTST, test class labels
opts	list with several parameter settings: gaussdim ... *Filename [* = s,g,x] from where to load the models (see sfaClassify)

Value

list res containing

res$errtrn	1 x 2 matrix: error rate with / w/o SFA on training set
res$errtst	1 x 2 matrix: error rate with / w/o SFA on test set
res$y	output from SFA when applied to training data
res$ytst	output from SFA when applied to test data
res$predT	predictions with SFA + GaussClassifier on test set
res$predX	predictions w/o SFA (only GaussClassifier) on test set (only if opts.xFilename exists)

See Also

sfaClassPredict sfaExecute

rSFA documentation built on March 29, 2022, 5:05 p.m.