htmd.clustering.regular module#
- class htmd.clustering.regular.RegCluster(radius=None, n_clusters=None)#
Bases:
BaseEstimator
,ClusterMixin
,TransformerMixin
Class to perform regular clustering of a given data set
RegCluster can be passed a radius or an approximate number of clusters. If a number of clusters is passed, KCenter clustering is used to estimate the necessary radius. RegCluster randomly chooses a point and assigns all points within the radius of this point to the same cluster. Then it proceeds with the nearest point, which is not yet assigned to a cluster and puts all unassigned points within the radius of this point in the next cluster and so on.
Examples
>>> cluster = RegCluster(radius=5.1) >>> cluster.fit(data)
- property clusterSize#
- property cluster_centers_#
- fit(data)#
performs clustering of data
- Parameters:
data (np.ndarray) – array of data points to cluster
merge (int) – minimal number of frames within each cluster. Smaller clusters are merged into next big one
- set_fit_request(*, data: bool | None | str = '$UNCHANGED$') RegCluster #
Configure whether metadata should be requested to be passed to the
fit
method.Note that this method is only relevant when this estimator is used as a sub-estimator within a meta-estimator and metadata routing is enabled with
enable_metadata_routing=True
(seesklearn.set_config()
). Please check the User Guide on how the routing mechanism works.The options for each parameter are:
True
: metadata is requested, and passed tofit
if provided. The request is ignored if metadata is not provided.False
: metadata is not requested and the meta-estimator will not pass it tofit
.None
: metadata is not requested, and the meta-estimator will raise an error if the user provides it.str
: metadata should be passed to the meta-estimator with this given alias instead of the original name.
The default (
sklearn.utils.metadata_routing.UNCHANGED
) retains the existing request. This allows you to change the request for some parameters and not others.New in version 1.3.
- datastr, True, False, or None, default=sklearn.utils.metadata_routing.UNCHANGED
Metadata routing for
data
parameter infit
.
- selfobject
The updated object.