Description Usage Arguments Details Value See Also Examples
Performs mixture discriminant analysis.
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subclasses |
numeric value or vector of subclasses per class. |
sub.df |
effective degrees of freedom of the centroids per class if subclass centroid shrinkage is performed. |
tot.df |
specification of the total degrees of freedom as an alternative
to |
dimension |
dimension of the discriminant subspace to use for prediction. |
eps |
numeric threshold for automatically truncating the dimension. |
iter |
limit on the total number of iterations. |
method |
regression function used in optimal scaling. The default of
linear regression is provided by |
trace |
logical indicating whether iteration information is printed. |
... |
additional arguments to |
factor
subclasses
The predict
function for this model additionally accepts the
following argument.
prior
prior class membership probabilities for prediction data if different from the training set.
Default values for the NULL
arguments and further model details can be
found in the source links below.
MLModel
class object.
mda
, predict.mda
,
fit
, resample
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