neuralset.extractors.meta.AggregatedExtractor

class neuralset.extractors.meta.AggregatedExtractor(*, event_types: str | tuple[str, ...] = 'Event', aggregation: Literal['single', 'sum', 'mean', 'first', 'middle', 'last', 'cat', 'stack', 'trigger'] = 'single', allow_missing: bool = False, frequency: Literal['native'] = 'native', extractors: list[BaseExtractor], extractor_aggregation: Literal['cat', 'stack', 'mean', 'sum'] = 'cat')

Aggregate multiple extractors along the specified dimension. Note that self.extractor_aggregation determines how the extractors are aggregated for a given event, whereas self.aggregation determines how different events are aggregated (after the extractors have been aggregated).