Feature overview table

Note that all catch22 features are statistical properties of the z-scored time series—they aim to focus on properties of the time-ordering of the data and are insensitive to the raw values in the time series.

In the table below we give the original feature name [from the Lubba et al. (2019) paper], and a shorter name more suitable for use in feature descriptions.

Features are also (loosely) categorized into broad conceptual groupings.

#Feature nameShort nameCategoryDescription
1

DN_HistogramMode_5

mode_5

5-bin histogram mode

2

DN_HistogramMode_10

mode_10

10-bin histogram mode

3

DN_OutlierInclude_p_001_mdrmd

outlier_timing_pos

Positive outlier timing

4

DN_OutlierInclude_n_001_mdrmd

outlier_timing_neg

Negative outlier timing

5

first1e_acf_tau

acf_timescale

6

firstMin_acf

acf_first_min

First minimum of the ACF

7

SP_Summaries_welch_rect_area_5_1

low_freq_power

Power in lowest 20% frequencies

8

SP_Summaries_welch_rect_centroid

centroid_freq

Centroid frequency

9

FC_LocalSimple_mean3_stderr

forecast_error

Error of 3-point rolling mean forecast

10

FC_LocalSimple_mean1_tauresrat

whiten_timescale

Change in autocorrelation timescale after incremental differencing

11

MD_hrv_classic_pnn40

high_fluctuation

Proportion of high incremental changes in the series

12

SB_BinaryStats_mean_longstretch1

stretch_high

Longest stretch of above-mean values

13

SB_BinaryStats_diff_longstretch0

stretch_decreasing

Longest stretch of decreasing values

14

SB_MotifThree_quantile_hh

entropy_pairs

Entropy of successive pairs in symbolized series

15

CO_HistogramAMI_even_2_5

ami2

Histogram-based automutual information (lag 2, 5 bins)

16

CO_trev_1_num

trev

Time reversibility

17

IN_AutoMutualInfoStats_40_gaussian_fmmi

ami_timescale

First minimum of the AMI function

18

SB_TransitionMatrix_3ac_sumdiagcov

transition_variance

Transition matrix column variance

19

PD_PeriodicityWang_th001

periodicity

Wang's periodicity metric

20

CO_Embed2_Dist_tau_d_expfit_meandiff

embedding_dist

Goodness of exponential fit to embedding distance distribution

21

SC_FluctAnal_2_rsrangefit_50_1_logi_prop_r1

rs_range

Rescaled range fluctuation analysis (low-scale scaling)

22

SC_FluctAnal_2_dfa_50_1_2_logi_prop_r1

dfa

Detrended fluctuation analysis (low-scale scaling)

And in some cases, in which scale and spread of the raw time-series values may be relevant to class differences, the two simple distributional moment features (using the catch24 flag in the software implemenations) can be added:

Feature nameShort nameDescription

DN_Mean

mean

Mean

DN_Spread_Std

std

Standard deviation

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