The LinearDiscriminantAnalysis
node in SciCraft has the
following node arguments:
- Input ports:
- X: Matrix containing the values for the calibration sample.
- y: Vector of integers or strings that specifies which
class the samples in the X matrix stems from. Hence the
Length of y must match the number of rows in X.
- Input arguments:
- none
- Output ports:
- calerror: Scalar containing the percentwise calibration
error for the classification rule.
- prederror: Scalar containing the percentwise prediction error
for the classification rule estimated using leave-one-out
cross-validation.
- rule: R-object containing the following elements:
- counts: List with size equal to the number of classes
in the input vector
where each element is an integer
that states the number of samples belonging the that class.
- lev: Vector of strings that states the names of the classes in
the input vector
.
- means: Matrix that contains the group means.
- N: Integer with the number of observations used.
- prior: List where each element states the prior
probability used for that class.
- Scaling: Vector or matrix which transforms observations
to discriminant functions, normalized so that within groups
covariance matrix is spherical.
- svd: Scalar or vector with the singular values, which give
the ratio of the between- and within-group standard deviations on
the linear discriminant variables. Their squares are the canonical
F-statistics
Bjørn Kåre Alsberg
2006-04-06