Event Prediction
First Claim
1. A method of predicting the outcome of a proposed event comprising:
- receiving a plurality of variables describing the proposed event;
for each variable, accessing stored statistics describing belief about values of a weight, the stored statistics having been learnt using a machine learning process comprising assumed density filtering;
combining the statistics;
mapping the combined statistics into a number representing the probability of the proposed event having a specified outcome by using a link function; and
storing the probability information for the proposed event.
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Accused Products
Abstract
There are many situations in which it is desired to predict outcomes of events. In an example, an event prediction system is described which receives variables for a proposed event. The system accesses learnt statistics describing belief about weights associated with the variables and uses the weights to determine probability information that the proposed event will have a specified outcome. The process involves combining the accessed statistics and mapping them into a number representing the probability. In another example, a machine learning process using assumed density filtering is used to learn the statistics from data about observed events. The event prediction system may be used as part of any suitable type of system such as an internet advertising system, an email filtering system, or a fraud detection system.
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Citations
20 Claims
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1. A method of predicting the outcome of a proposed event comprising:
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receiving a plurality of variables describing the proposed event; for each variable, accessing stored statistics describing belief about values of a weight, the stored statistics having been learnt using a machine learning process comprising assumed density filtering; combining the statistics; mapping the combined statistics into a number representing the probability of the proposed event having a specified outcome by using a link function; and storing the probability information for the proposed event. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. A method of predicting the outcome of a proposed event comprising:
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carrying out a training process using assumed density filtering in order to learn statistics describing belief about values of weights; receiving a plurality of variables describing the proposed event; for each variable, accessing statistics from the training process describing belief about values of a weight; combining the statistics; mapping the combined statistics into a number representing the probability of the proposed event having a specified outcome by using a link function; and
storing the probability information for the proposed event. - View Dependent Claims (12, 13, 14, 15, 16, 17, 18, 19)
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20. One or more device-readable media with device-executable instructions for performing steps comprising:
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receiving a plurality of variables describing a proposed event; for each variable, accessing stored statistics describing belief about values of a weight, the stored statistics having been learnt using a machine learning process comprising assumed density filtering; combining the statistics; mapping the combined statistics into a number representing the probability of the proposed event having a specified outcome by using a link function; and storing the probability information for the proposed event.
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Specification