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All Projects → statefb → singular-spectrum-transformation

statefb / singular-spectrum-transformation

Licence: MIT license
fast implementation of singular spectrum transformation (change point detection algorithm)

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Jupyter Notebook
11667 projects
python
139335 projects - #7 most used programming language

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time-serieschangepointanomaly-detection

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Build Status

SST (Singular Spectrum Transformation)

A fast implementation of Singular Spectrum Transformation for python.

What is SST?

A change point detection algorithm. example example see more examples

Features

fast computation

  • efficient algorithm using Lanczos method
  • Numba

Installation

$pip install fastsst

Basic Usage

from fastsst import SingularSpectrumTransformation

sst = SingularSpectrumTransformation(win_length=30)

"""
note:
 - data must be 1d np.ndarray
 - the first run takes a few seconds for jit compling
"""
score = sst.score_offline(data)

Others

TODO

  • online evaluation

References

  1. Tsuyoshi Ide, Koji Tsuda, Change-Point Detection using Krylov Subspace Learning, SIAM International Conference on Data Mining, pp.515-520, 2007
  2. Tsuyoshi Ide, Speeding up Change-Point Detection using Matrix Compression (Japanse), Workshop on Information-Based Induction Sciences, 2006
  3. Tsuyoshi Ide, Masashi Sugiyama, Anomaly Detection and Change Detection (Japanse), Kodansha, 2015
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