An object with class "cluster_fit" is a container for information about a model that has been fit to the data.
Details
The following model types are implemented in tidyclust:
K-Means in
k_means()
Hierarchical (Agglomerative) Clustering in
hier_clust()
The main elements of the object are:
spec
: Acluster_spec
object.fit
: The object produced by the fitting function.preproc
: This contains any data-specific information required to process new a sample point for prediction. For example, if the underlying model function requires argumentsx
and the user passed a formula tofit
, thepreproc
object would contain items such as the terms object and so on. When no information is required, this isNA
.
As discussed in the documentation for cluster_spec
, the original
arguments to the specification are saved as quosures. These are evaluated for
the cluster_fit
object prior to fitting. If the resulting model object
prints its call, any user-defined options are shown in the call preceded by a
tilde (see the example below). This is a result of the use of quosures in the
specification.
This class and structure is the basis for how tidyclust stores model objects after seeing the data and applying a model.