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Application US20190066130
Published 2019-02-28
Unified Artificial Intelligence Model For Multiple Customer Value Variable Prediction
A unified model for a neural network can be used to predict a particular value, such as a customer value. In various instances, customer value may have particular sub-components. Taking advantage of this fact, a specific learning architecture can be used to predict not just customer value (e.g. a final objective) but also the sub-components of customer value. This allows improved accuracy and reduced error in various embodiments.
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- 1. A method for creating a unified model for predicting customer value using artificial intelligence, comprising:
creating, at a computer system, a series of two or more neural network modules, each of the neural network modules including a dense layer of neurons connected to all of the neurons for the immediately preceding neural network module; creating, at the computer system, a plurality of variable sub-task neural network modules, wherein each of the variable sub-task neural network modules is connected to an output of the last of the series of two or more neural network modules, and wherein each of the variable sub-task neural network modules is configured to calculate a separate one of a plurality of component variables for predicted customer value; and creating, at the computer system, a final task neural network module for calculating predicted customer value, wherein the final task neural network module is connected to the output of the last of the series of two or more neural network modules and is also connected to an intermediate output from each of the plurality of variable sub-task neural network modules; wherein the unified model is configured to predict, using particular input data pertaining to a particular customer, each of the plurality of component variables for predicted customer value and also separately predict total customer value for that customer.
- 11. A non-transitory computer-readable medium having stored thereon instructions that are executable by a computer system to cause the computer system to perform operations comprising:
creating a series of two or more neural network modules, each of the neural network modules including a dense layer of neurons connected to all of the neurons for the immediately preceding neural network module; creating a plurality of variable sub-task neural network modules, wherein each of the variable sub-task neural network modules is connected to an output of the last of the series of two or more neural network modules, and wherein each of the variable sub-task neural network modules is configured to calculate a separate one of a plurality of component variables for predicted customer value; and creating a final task neural network module for calculating predicted customer value, wherein the final task neural network module is connected to the output of the last of the series of two or more neural network modules and is also connected to an intermediate output from each of the plurality of variable sub-task neural network modules; wherein the unified model is configured to predict, using particular input data pertaining to a particular customer, each of the plurality of component variables for predicted customer value and also separately predict total customer value for that customer.
- 17. A computer system, comprising:
a processor; and one or more computer-readable media having stored thereon instructions that are executable to cause the computer system to perform operations comprising:
creating a series of two or more neural network modules, each of the neural network modules including a dense layer of neurons connected to all of the neurons for the immediately preceding neural network module;
creating a plurality of variable sub-task neural network modules, wherein each of the variable sub-task neural network modules is connected to an output of the last of the series of two or more neural network modules, and wherein each of the variable sub-task neural network modules is configured to calculate a separate one of a plurality of component variables for predicted customer value; and
creating a final task neural network module for calculating predicted customer value, wherein the final task neural network module is connected to the output of the last of the series of two or more neural network modules and is also connected to an intermediate output from each of the plurality of variable sub-task neural network modules;
wherein the unified model is configured to predict, using particular input data pertaining to a particular customer, each of the plurality of component variables for predicted customer value and also separately predict total customer value for that customer.
