sfaClassPredict {rSFA}R Documentation

Predict Class for SFA classification

Description

Use a SFA classification model (stored in opts$*Filename), predict & evaluate on new data (xtst,realc_tst).
Author of orig. matlab version: Wolfgang Konen, Jan 2011-Mar 2011.
See also [Berkes05] Pietro Berkes: Pattern recognition with Slow Feature Analysis. Cognitive Sciences EPrint Archive (CogPrint) 4104, http://cogprints.org/4104/ (2005)

Usage

sfaClassPredict(xtst, realcTst, opts)

Arguments

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$errtst

1 x 2 matrix: error rate with / w/o SFA on test set

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

sfaClassify sfaExecute


[Package rSFA version 1.5 Index]