A function that applies the model to predict outcomes on new test data.
data
A matrix containing the training data.
status
A vector containing the training outcomes, which should either be a
binary-valued factor or a numeric vector of contiuous outcomes.
details
A list of the fitted parameters for the specified model.
...
Any extra information that is produced while learning the model; these
wil be saved in the extras slot of the FittedModel object.
Author
Kevin R. Coombes <krc@silicovore.com.
Details
Most users will never need to use this function; instead, they will
first use an existing object of the Modeler-class,
call the learn method of that object with the training data
to obtain a FittedModel object, and then apply its
predict method to test data. Only people who want to
implement the learn-predict interface for a new classification algorithm
are likely to need to call this function directly.
See Also
See the descriptions of the learn function and
the predict method for details on how to fit models on
training data and make predictions on new test data.
See the description of the Modeler-class for details
about the kinds of objects produced by learn.