Segmentation

Time series segmentation involves partitioning a series into regions that are dissimilar to neighboring regions. The aeon.segmentation module contains algorithms and tools for time series segmentation.

BinSegmenter([n_cps, model, min_size, jump])	BinSeg (Binary Segmentation) Segmenter.
ClaSPSegmenter([period_length, n_cps, ...])	ClaSP (Classification Score Profile) Segmentation.
FLUSSSegmenter([period_length, n_regimes, ...])	FLUSS (Fast Low-cost Unipotent Semantic Segmentation) Segmenter.
InformationGainSegmenter([k_max, step])	Information Gain based Temporal Segmentation (GTS) Estimator.
GreedyGaussianSegmenter([k_max, lamb, ...])	Greedy Gaussian Segmentation Estimator.
EAggloSegmenter([member, alpha, penalty])	Hierarchical agglomerative estimation of multiple change points.
HMMSegmenter(emission_funcs, transition_prob_mat)	Implements a simple HMM fitted with Viterbi algorithm.
HidalgoSegmenter([metric, K, zeta, q, ...])	Heteregeneous Intrinsic Dimensionality Algorithm (Hidalgo) model.
RandomSegmenter([random_state, n_segments])	Random Segmenter.

Base

BaseSegmenter(axis[, n_segments])

Base class for segmentation algorithms.