Timeseries Features DSLedit

Defines how time series data must be aggregated into features for learning and inference.

The list below defines the aggregation operators can be used to define features. These values can be extracted by using numeric fields in the data source documents.


This version does not support feature generation by a provided script, nor extracting features from non numeric fields.

The operators that are returned consist of: count, min, max, sum, avg, sum_of_squares, variance, and std_deviation.


This version supports the count and avg operators with InfluxDb. Additional operators will be added in a future version.