Description Usage Arguments Details Value See Also
Classify multivariate observations in conjunction with
ossvm
.
1 2 3 4 |
object |
Object of class |
newdata |
An object containing the new input data:
either a matrix or a sparse matrix (object of class
|
decision.values |
Logical controlling whether the decision values of all binary classifiers computed in multiclass classification shall be computed and returned. |
probability |
Logical indicating whether class probabilities should be computed and returned. |
... |
Further arguments. |
na.action |
A function to specify the action to be taken if 'NA's are found. The default action is na.omit, which leads to rejection of cases with missing values on any required variable. An alternative is na.fail, which causes an error if NA cases are found. (NOTE: If given, this argument must be named.) |
This function is a method for the generic function
predict()
for class "ossvm"
. It can be
invoked by calling predict(x)
for an object
x
of the appropriate class, or directly by calling
predict.ossvm(x)
regardless of the class of the
object.
A vector of predicted values (for classification: a
vector of labels, for density estimation: a logical
vector). If decision.value
is TRUE
, the
vector gets a "decision.values"
attribute
containing a n * c matrix (n number of
predicted values, c number of classifiers) of all
c binary classifiers' decision values. There are
k * (k - 1) / 2 classifiers (k number of
classes). The colnames of the matrix indicate the labels
of the two classes. If probability
is TRUE
,
the vector gets a "probabilities"
attribute
containing a n * k matrix (n number of
predicted values, k number of classes) of the class
probabilities.
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