tsseg.algorithms.patss package

PaTSS — Pattern-based Time Series Segmentation.

Description

PaTSS detects states in time series by mining frequent temporal patterns, building a pattern-based embedding matrix, and clustering the resulting features. The pipeline consists of three stages:

1. Pattern mining — extracts frequent sub-patterns from the series using configurable length, frequency and overlap parameters.

2. Embedding — constructs a binary or frequency-based embedding matrix where each row is a time step and each column a mined pattern.

3. Segmentation — applies a segmentation algorithm (default: logistic regression classifier) on the embedding to partition the series into states.

All configuration is passed through a config dictionary.

Type: state detection

Supervision: fully unsupervised

Scope: univariate and multivariate

Parameters

Name	Type	Default	Description
config	dict / None	None	Settings for PaTSS. If None, default hyperparameters are used. Keys include "pattern_length", "min_frequency", "max_overlap", "n_segments" and classifier settings.
axis	int	0	Time axis (input assumed (n_timepoints, n_channels)).

Usage

from tsseg.algorithms import PatssDetector

detector = PatssDetector()       # default config
states = detector.fit_predict(X)

# Custom config
detector = PatssDetector(config={"pattern_length": 20, "n_segments": 5})
states = detector.fit_predict(X)

Implementation: Adapted from the original PaTSS code.

Reference: —

Subpackages

• tsseg.algorithms.patss.algorithms package
  • Submodules
  • tsseg.algorithms.patss.algorithms.ClaSP module
  • tsseg.algorithms.patss.algorithms.FLOSS module
  • tsseg.algorithms.patss.algorithms.PaTSS module
  • tsseg.algorithms.patss.algorithms.PaTSS_perso module
  • Module contents
• tsseg.algorithms.patss.embedding package
  • Submodules
  • tsseg.algorithms.patss.embedding.FrequentPatternMiningEmbedder module
  • tsseg.algorithms.patss.embedding.PatternBasedEmbedder module
  • tsseg.algorithms.patss.embedding.PatternBasedEmbedding module
  • tsseg.algorithms.patss.embedding.embedding_matrix module
  • tsseg.algorithms.patss.embedding.pattern_filter module
  • tsseg.algorithms.patss.embedding.pattern_mining module
  • Module contents
• tsseg.algorithms.patss.segmentation package
  • Submodules
  • tsseg.algorithms.patss.segmentation.LogisticRegressionSegmentor module
  • tsseg.algorithms.patss.segmentation.Segmentor module
  • Module contents

Submodules

tsseg.algorithms.patss.detector module

Module contents