sfaExecute: Execute learned function for input data

In rSFA: Slow Feature Analysis

Execute learned function for input data

Description

After completion of the learning phase (step="sfa") this function can be used to apply the learned function to the input data.
The execution is completed in 4 steps:
1. projection on the input principal components (dimensionality reduction)
2. expansion (if necessary)
3. projection on the whitened (expanded) space
4. projection on the slow functions

Usage

sfaExecute(sfaList, DATA, prj = NULL, ncomp = NULL)

Arguments

sfaList	A list that contains all information about the handled sfa-structure
DATA	Input data, each column a different variable
prj	If not NULL, the preprocessing step 1 is skipped for SFA2
ncomp	number of learned functions to be used

Value

matrix DATA containing the calculated output

See Also

sfa2 sfa1 sfaStep

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