fdaCMA-methods: Fisher's Linear Discriminant Analysis
Description
Fisher's Linear Discriminant Analysis constructs a subspace of
'optimal projections' in which classification is performed.
The directions of optimal projections are computed by the
function cancor from the package stats. For
an exhaustive treatment, see e.g. Ripley (1996).
Arguments
Methods
X = "matrix", y = "numeric", f = "missing"
signature 1
X = "matrix", y = "factor", f = "missing"
signature 2
X = "data.frame", y = "missing", f = "formula"
signature 3
X = "ExpressionSet", y = "character", f = "missing"
signature 4
For references, further argument and output information, consult
fdaCMA.
