Event-based feature engineering

A system comprising:

• a computing node configured at least to:
• receive information indicative of one or more selected entities of a plurality of entities;
• receive information indicative of selecting a first event associated with the one or more selected entities, the first event indicative of when a value associated with a second event is predicted;
• receive an indication of the second event, the second event indicative of selecting a label value associated with the second event;
• extract from data indicative of events associated with the plurality of entities, data associated with the first event and the second event;
• and
• generate, using the data associated with the first event and the second event, one or more feature vectors or examples for use with a machine learning algorithm, the one or more feature vectors or examples comprising the values of one or more predictor features associated with a selected entity among the plurality of entities proximate to the first event and the values of one or more label features associated with a selected entity among the plurality of entities proximate to the second event.

A non-transitory computer-readable medium storing instructions that, when executed, cause operations comprising:

• receiving an indication of one or more selected entities of the plurality of entities;
• receiving information indicative of selecting one or more prediction times associated with each of the one or more selected entities;
• receiving information indicative of selecting one or more label times associated with each of the one or more selected entities, each of the one or more label times corresponding to at least one of the one or more prediction times, wherein the one or more label times occur after the corresponding one or more prediction times;
• extracting, from the data indicative of events associated with the plurality of entities, data associated with the one or more prediction times and the one or more label times;
• and
• generating, using the data associated with the one or more prediction times and the one or more label times, one or more feature vectors or examples for use with a machine learning algorithm, the one or more feature vectors or examples comprising values of one or more predictor features associated with the one or more selected entities at the one or more prediction times and values of one or more label features associated with the one or more selected entities at the one or more label times.