Clustering

The aeon.clustering module contains algorithms for time series clustering.

All clusterers in aeon can be listed using the aeon.registry.all_estimators utility, using estimator_types=”clusterer”, optionally filtered by tags. Valid tags can be listed using aeon.registry.all_tags.

Deep learning

BaseDeepClusterer([n_clusters, estimator, ...])	Abstract base class for deep learning time series clusterers.
AEFCNClusterer([n_clusters, estimator, ...])	Auto-Encoder based Fully Convolutional Network (FCN), as described in [R4f194d8f8b22-1].
AEResNetClusterer([n_clusters, estimator, ...])	Auto-Encoder with Residual Network backbone for clustering.

Clustering Algorithms

TimeSeriesKMeans([n_clusters, ...])	Time series K-means clustering implementation.
TimeSeriesKMedoids([n_clusters, ...])	Time series K-medoids implementation.
TimeSeriesKShapes(*args, **kwargs)	Kshape algorithm: wrapper of the tslearn implementation.
TimeSeriesKShape([n_clusters, ...])	Kshape algorithm: wrapper of the tslearn implementation.
TimeSeriesKernelKMeans([n_clusters, kernel, ...])	Kernel K Means [R3e7c374b18c1-1]: wrapper of the tslearn implementation.
TimeSeriesCLARA([n_clusters, ...])	Time series CLARA implementation.
TimeSeriesCLARANS([n_clusters, ...])	Time series CLARANS implementation.

Base

BaseClusterer([n_clusters])

Abstract base class for time series clusterers.