DatasetsEvaluation

Aggregation Steps - Datasets

This document outlines a series of aggregation steps used for aggregating EKGs of different datasets and the resulting performances.

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Soccer

Steps:

step1 = AggrStep(aggr_type="ENTITIES", ent_type="playerId", group_by=["role"], 
            where="birthYear > 1990", attr_aggrs=[])

step2 = AggrStep(aggr_type="ENTITIES", ent_type="pos_orig", 
            group_by=["zone"], where=None, attr_aggrs=[])

step3 = AggrStep(aggr_type="EVENTS", ent_type=None, where='matchId = "2575959"', 
            group_by=[log.event_activity, "teamId", "playerId"], 
            attr_aggrs=[AttrAggr(name=log.event_timestamp, function=AggregationFunction.MINMAX),
                    AttrAggr(name="teamId", function=AggregationFunction.MULTISET)])

step4 = AggrStep(aggr_type="EVENTS", ent_type=None, where='matchId <> "2575959"', 
            group_by=[log.event_activity, "teamId", "playerId"], 
            attr_aggrs=[AttrAggr(name=log.event_timestamp, function=AggregationFunction.MINMAX),
            AttrAggr(name="teamId", function=AggregationFunction.MULTISET)])

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Tip

These aggregation steps are just examples. Thanks to the modular nature of the approach, you can combine and adapt them to construct a variety of queries over entity and event data.