predict.fda
From mda v0.48
by Trevor Hastie
Classify by Flexible Discriminant Analysis
Classify observations in conjunction with fda
.
 Keywords
 classif
Usage
"predict"(object, newdata, type, prior, dimension, ...)
Arguments
 object
 an object of class
"fda"
.  newdata
 new data at which to make predictions. If missing, the training data is used.
 type
 kind of predictions:
type = "class"
(default) produces a fitted factor,type = "variates"
produces a matrix of discriminant (canonical) variables,type = "posterior"
produces a matrix of posterior probabilities (based on a gaussian assumption), andtype = "hierarchical"
produces the predicted class in sequence for models of all dimensions.  prior
 the prior probability vector for each class; the default is the training sample proportions.
 dimension
 the dimension of the space to be used, no larger
than the dimension component of
object
.  ...
 further arguments to be passed to or from methods.
Value

An appropriate object depending on
type
. object
has a
component fit
which is regression fit produced by the
method
argument to fda
. There should be a
predict
method for this object which is invoked. This method
should itself take as input object
and optionally newdata
.
See Also
Examples
data(iris)
irisfit < fda(Species ~ ., data = iris)
irisfit
## Call:
## fda(x = iris$x, g = iris$g)
##
## Dimension: 2
##
## Percent BetweenGroup Variance Explained:
## v1 v2
## 99.12 100
confusion(predict(irisfit, iris), iris$Species)
## Setosa Versicolor Virginica
## Setosa 50 0 0
## Versicolor 0 48 1
## Virginica 0 2 49
## attr(, "error"):
## [1] 0.02
Community examples
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