Setup ICA config.
setup_ICA(
k = 3L,
type = "parallel",
fun = "logcosh",
alpha = 1,
row_norm = TRUE,
maxit = 100L,
tol = 1e-04,
features = NULL
)ICAConfig object.
Integer [1, Inf): Number of components.
Character {"parallel", "deflation"}: Type of ICA.
Character {"logcosh", "exp"}: ICA function.
Numeric [1, 2]: Used in approximation to neg-entropy with fun = "logcosh".
Logical: If TRUE, standardize each case across features
before ICA, i.e. subtract each case's mean and divide by its standard
deviation. Appropriate when the features share units and each case's overall
level and scale are a nuisance rather than signal, as for spectra or assays
whose total intensity varies by sample. It spends two degrees of freedom per
case, so its cost is roughly
2 / ncol(x): negligible for hundreds of features, but substantial for a
handful, where each case's level and scale are more likely to be signal.
Set FALSE for narrow or mixed-unit data.
Integer [1, Inf): Maximum number of iterations.
Numeric [0, Inf): Tolerance.
Optional Character vector: Names of at least 2 distinct
feature columns to decompose. NULL decomposes all numeric features.
EDG
ica_config <- setup_ICA(k = 3L)
ica_config
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