Description Objects from the Class Slots Methods Author(s) See Also Examples
Objects of this class represent parametrized statistical
models (of the Modeler-class
) after they have been fit
to a training data set. These objects can be used to
predict
binary outcomes on new test data sets.
Objects can be created by calls to the constructor function,
FittedModel
. In practice, however, most
FittedModel
objects are created as the result of applying the
learn
function to an object of the
Modeler-class
.
predictFunction
:Object of class "function"
that
implemnts the ability to make predictions using the fitted model.
trainData
:Object of class "matrix"
containing
the trainng data set. Rowes are features and columns are samples.
trainStatus
:Object of class "vector"
. Should
either be a numeric vector representing outcome or a factor with two
levels, containing the classes of the training data set.
details
:Object of class "list"
containing the
fitted parameters for the specific model.
extras
:Object of class "list"
containing any
extra information (such as diagnostics) produced a a result of
learning the model from the training data set.
fsVector
:Logical vector indicating which features should be retained (TRUE) of discared (FALSE) after performing featgure selection on the training data.
signature(object = "FittedModel")
: Predict the
binary outcome on a new data set.
Kevin R. Coombes <krcoombes@mdanderson.org>
See Modeler-class
and learn
for details on
how to fit a model to data.
1 | showClass("FittedModel")
|
Loading required package: ClassDiscovery
Loading required package: cluster
Loading required package: oompaBase
Loading required package: ClassComparison
Class "FittedModel" [package "Modeler"]
Slots:
Name: predictFunction trainData trainStatus details
Class: function matrix numericOrFactor list
Name: extras fsVector
Class: list logical
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.