| TSClusters-class {dtwclust} | R Documentation |
Class definition for TSClusters and derived classes
Description
Formal S4 classes for time-series clusters. See class hierarchy and slot organization at the bottom.
Details
The base class is TSClusters. The 3 classes that inherit from it are: PartitionalTSClusters,
HierarchicalTSClusters and FuzzyTSClusters.
HierarchicalTSClusters also contain stats::hclust() as parent class.
Package clue is supported, but generics from flexclust are not. See also TSClusters-methods.
Slots
callThe function call.
familyAn object of class tsclustFamily.
controlAn appropriate control object for
tsclust(). See tsclust-controls.datalistThe provided data in the form of a list, where each element is a time series.
typeA string indicating one of the supported clustering types of
tsclust().distanceA string indicating the distance used.
centroidA string indicating the centroid used.
preprocA string indicating the preprocessing used.
kInteger indicating the number of desired clusters.
clusterInteger vector indicating which cluster a series belongs to (crisp partition). For fuzzy clustering, this is based on distance, not on
fcluster. For hierarchical, this is obtained by callingstats::cutree()with the given value ofk.centroidsA list with the centroid time series.
distmatIf computed, the cross-distance matrix.
proctimeTime during function execution, as measured with
base::proc.time().dotsThe contents of the original call's ellipsis (...).
argsThe contents of the original call's
argsparameter. Seetsclust_args().seedThe random seed that was used.
iterThe number of iterations used.
convergedA logical indicating whether the function converged.
clusinfoA data frame with two columns:
sizeindicates the number of series each cluster has, andav_distindicates, for each cluster, the average distance between series and their respective centroids (crisp partition).cldistA column vector with the distance between each series in the data and its corresponding centroid (crisp partition).
methodA string indicating which hierarchical method was used.
fclusterNumeric matrix that contains membership of fuzzy clusters. It has one row for each series and one column for each cluster. The rows must sum to 1. Only relevant for fuzzy clustering.
TSClusters
The base class contains the following slots:
-
call -
family -
control -
datalist -
type -
distance -
centroid -
preproc -
k -
cluster -
centroids -
distmat -
proctime -
dots -
args -
seed
PartitionalTSClusters
This class adds the following slots to the base class:
-
iter -
converged -
clusinfo -
cldist
HierarchicalTSClusters
This class adds the following slots to the base class:
-
method -
clusinfo -
cldist
FuzzyTSClusters
This class adds the following slots to the base class:
-
iter -
converged -
fcluster