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Application US20200279160
Published 2020-09-03
System And Method For Multi-task Learning
A method of generating a multi-modal prediction is disclosed herein. A computing system retrieves event data from a data store. The event data includes information for a plurality of events across a plurality of seasons. Computing system generates a predictive model using a mixture density network, by generating an input vector from the event data learning, by the mixture density network, a plurality of values associated with a next play following each play in the event data. The mixture density network is trained to output the plurality of values near simultaneously. Computing system receives a set of event data directed to an event in a match. The set of event data includes information directed to at least playing surface position and current score. Computing system generates, via the predictive model, a plurality of values associated with a next event following the event based on the set of event data.
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- 1. A method of generating a multi-modal prediction, comprising:
retrieving, by a computing system, event data from a data store, the event data comprising information for a plurality of events across a plurality of seasons; generating, by the computing system, a predictive model using a mixture density network, by:
generating an input vector from the data, the input vector comprising one or more parameters associated with each play in the event data; and
learning, by the mixture density network, a plurality of values associated with a next play following each play in the event data, wherein the mixture density network is trained to output the plurality of values near simultaneously;
receiving, by the computing system, a set of data directed to an event in a match, the set of data comprising information directed to at least playing surface position and current score; and generating, by the computing system via the predictive model, a plurality of values associated with a next event following the event based on the set of data, wherein the plurality of values is determined near simultaneously.
- 8. A system for generating a multi-modal prediction, comprising:
a processor; and a memory having programming instructions stored thereon, which, when executed by the processor, performs one or more operations, comprising: retrieving, by a computing system, data from a data store, the data comprising information for a plurality of events across a plurality of seasons; generating a predictive model using a mixture density network, by:
generating an input vector from the data, the input vector comprising one or more parameters associated with each play in the event data; and
learning, by the mixture density network, a plurality of values associated with a next play following each play in the event data, wherein the mixture density network is trained to output the plurality of values near simultaneously;
receiving a set of data directed to an event in a match, the set of data comprising information directed to at least playing surface position and current score; and generating, via the predictive model, a plurality of values associated with a next event following the event based on the set of data, wherein the plurality of values are determined near simultaneously.
- 15. A non-transitory computer readable medium including one or more sequences of instructions that, when executed by the one or more processors, causes:
retrieving, by a computing system, event data from a data store, the event data comprising information for a plurality of events across a plurality of seasons; generating, by the computing system, a predictive model using a mixture density network, by:
generating an input vector from the data, the input vector comprising one or more parameters associated with each play in the event data; and
learning, by the mixture density network, a plurality of values associated with a next play following each play in the event data, wherein the mixture density network is trained to output the plurality of values near simultaneously;
receiving, by the computing system, a set of data directed to an event in a match, the set of data comprising information directed to at least playing surface position and current score; and generating, by the computing system via the predictive model, a plurality of values associated with a next event following the event based on the set of data, wherein the plurality of values are determined near simultaneously.
