fdaCMA-methods: Fisher's Linear Discriminant Analysis

In CMA: Synthesis of microarray-based classification

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).

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.

CMA documentation built on Nov. 8, 2020, 5:02 p.m.