Feature Calculation

Overview on extracted feature

tsfresh already calculates a comprehensive number of features. If you are interested which features are calculated just go to our

tsfresh.feature_extraction.feature_calculators

module. You will find the documentation of every calculated feature there.

Feature naming

tsfresh enforces a strict naming of the created features, which you have to follow whenever you create new feature calculators. This is due to the tsfresh.feature_extraction.FeatureExtractionSettings.from_columns() method which needs to deduce the following information from the feature name

  • the time series that was used to calculate the feature
  • the feature calculator method that was used to derive the feature
  • all parameters that have been used to calculate the feature (optional)

Hence, to enable the tsfresh.feature_extraction.FeatureExtractionSettings.from_columns() to deduce all the necessary conditions, the features will be named in the following format

{time_series_name}__{feature_name}__{parameter name 1}_{parameter value 1}__[..]__{parameter name k}_{parameter value k}

(Here we assumed that {feature_name} has k parameters).

Examples for feature naming

So for example the following feature name

temperature_1__quantile__q_0.6

is the value of the feature tsfresh.feature_extraction.feature_calculators.quantile() for the time series `temperature_1` and a parameter value of q=0.6. On the other hand, the feature named

Pressure 5__cwt_coefficients__widths_(2, 5, 10, 20)__coeff_14__w_5

denotes the value of the feature tsfresh.feature_extraction.feature_calculators.cwt_coefficients() for the time series `Pressure 5` under parameter values of widths=(2, 5, 10, 20), coeff=14 and w=5.