Method of building predictive models on transactional data

Details Method of building predictive models on transactional data Method of building predictive models on transactional data

2005-03-29

2005-03-29

Knight, Anthony (Department: 2121)

Data processing: artificial intelligence

Neural network

Learning task

Reexamination Certificate

active

06873979

ABSTRACT:
A method of building predictive statistical models provides a dedicated aggregation module for each transactional record source. Each aggregation module aggregates the transactional records using a neural network function to produce a scalar output which can then be input to a traditional modeling function, which may employ either logistic regression, neural network, or radial basis function techniques. The output of the aggregation modules can be saved, and updated aggregation values can be updated by processing new transaction records and combining the new transaction values with the previous output values using a blending function. Parameters of the neural network in the aggregation module may be calculated simultaneously with the parameters of the traditional modeling module.

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