Highly comparative analyses often involve classification tasks, in which each observation is assigned a (numeric) class label. Once data has been retrieved, as described above, class labels can be assigned to each time series in a dataset, and stored in the local
HCTSA*.mat files using the function
The example below assigns labels to two groups of time series in the
HCTSA.mat (specifying the shorthand
'raw' for this default, un-normalized data), corresponding to those labeled as 'parkinsons' and those labeled as 'healthy':
The first input is a cell specifying the keyword string to use to match each group.
To automatically detect unique keywords for labelling,
TS_LabelGroups can be run with an empty first input, as
By default, this function saves the group indices back to the data file (in this example,
HCTSA.mat), by adding a new field,
Group, to the
TimeSeries metadata table, which contains the group index of each time series.
Group indices stay with the time series they are assigned to after filtering and normalizing the data (using
TS_normalize). Group labels can be reassigned at any time by re-running the
Group labels are used by a range of analysis functions, including