| predict.fda(mda) | R Documentation |
predict.fda(object, x, type, prior, dimension)
object |
An object of class fda. |
x |
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 variables, type = posterior
produces a matrix of posterior probabilities (based on a
gaussian assumption), and type=hierarchical produces the
predicted class in sequence for models of all dimensions. |
prior |
the prior probabability 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. |
An appropriate object depending on type. object has a
component "fit"
fda,
mars,
bruto,
polyreg,
softmax,
confusion
data(iris) irisfit <- fda(Species ~ ., data = iris) irisfit ## Call: ## fda(x = iris$x, g = iris$g) ## ## Dimension: 2 ## ## Percent Between-Group 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