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catch22 Features
  • Overview
  • Feature overview table
  • catch22
    • Distribution shape
    • Extreme event timing
    • Linear autocorrelation structure
    • Nonlinear autocorrelation
    • Symbolic
    • Incremental differences
    • Simple forecasting
    • Self-affine scaling
    • Other
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  1. catch22

Other

embedding_dist

Naming info: This feature matches the hctsa feature called CO_Embed2_Dist_tau_d_expfit_meandiff.

This feature first represents the time series in a two-dimensional time-delay embedding space (using a time delay equal to the first zero-crossing of the autocorrelation function). It then computes successive distances between points in this 2D embedding space and analyzes the probability distribution of these distances. This feature outputs the mean absolute error of an exponential fit to this distribution. It will give low values to time series where the probability distribution of the distance between consecutive time-series values in the 2D embedding space is well approximated by an exponential distribution.

PreviousSelf-affine scaling

Last updated 1 year ago

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