Feature overview table
Note that all catch22 features are statistical properties of the zscored time series—they aim to focus on properties of the timeordering 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 name  Short name  Category  Description 

1 

 5bin histogram mode  
2 

 10bin histogram mode  
3 

 Positive outlier timing  
4 

 Negative outlier timing  
5 

 
6 

 First minimum of the ACF  
7 

 Power in lowest 20% frequencies  
8 

 Centroid frequency  
9 

 Error of 3point rolling mean forecast  
10 

 Change in autocorrelation timescale after incremental differencing  
11 

 Proportion of high incremental changes in the series  
12 

 Longest stretch of abovemean values  
13 

 Longest stretch of decreasing values  
14 

 Entropy of successive pairs in symbolized series  
15 

 Histogrambased automutual information (lag 2, 5 bins)  
16 

 Time reversibility  
17 

 First minimum of the AMI function  
18 

 Transition matrix column variance  
19 

 Wang's periodicity metric  
20 

 Goodness of exponential fit to embedding distance distribution  
21 

 Rescaled range fluctuation analysis (lowscale scaling)  
22 

 Detrended fluctuation analysis (lowscale scaling) 
And in some cases, in which scale and spread of the raw timeseries 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 name  Short name  Description 


 Mean 

 Standard deviation 
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