orion.Orion.detect

Orion.detect(data, visualization=False)[source]

Detect anomalies in the given data..

If visualization=True, also return the visualization outputs from the MLPipeline object.

Parameters

  • data (DataFrame) – Input data, passed as a pandas.DataFrame containing exactly two columns: timestamp and value.

  • visualization (bool) – If True, also capture the visualization named output from the MLPipeline and return it as a second output.

Returns

If visualization is False, it returns the events DataFrame. If visualization is True, it returns a tuple containing the events DataFrame followed by the visualization outputs dict.

Return type

DataFrame or tuple

orion.Orion.fit orion.Orion.evaluate