Goal-oriented clustering
First Claim
1. A computer-implemented method operable on a plurality of variables having a predetermined representation, the plurality of variables including a plurality of input-only variables, a plurality of output-only variables, and a plurality of both input-and-output variables, the method comprising:
- generating a model comprising a bottleneck architecture, the model including a top layer of nodes including at least the plurality of input-only variables, at least one middle layer of discrete hidden nodes, and a bottom layer of nodes including the plurality of output-only variables and the plurality of input-and-output variables; and
,determining at least one cluster from the model.
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Accused Products
Abstract
Clustering for purposes of data visualization and making predictions is disclosed. Embodiments of the invention are operable on a number of variables that have a predetermined representation. The variables include input-only variables, output-only variables, and both input-and-output variables. Embodiments of the invention generate a model that has a bottleneck architecture. The model includes a top layer of nodes of at least the input-only variables, one or more middle layer of hidden nodes, and a bottom layer of nodes of the output-only and the input-and-output variables. At least one cluster is determined from this model. The model can be a probabilistic neural network and/or a Bayesian network.
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Citations
34 Claims
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1. A computer-implemented method operable on a plurality of variables having a predetermined representation, the plurality of variables including a plurality of input-only variables, a plurality of output-only variables, and a plurality of both input-and-output variables, the method comprising:
- generating a model comprising a bottleneck architecture, the model including a top layer of nodes including at least the plurality of input-only variables, at least one middle layer of discrete hidden nodes, and a bottom layer of nodes including the plurality of output-only variables and the plurality of input-and-output variables; and
,determining at least one cluster from the model. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15)
- generating a model comprising a bottleneck architecture, the model including a top layer of nodes including at least the plurality of input-only variables, at least one middle layer of discrete hidden nodes, and a bottom layer of nodes including the plurality of output-only variables and the plurality of input-and-output variables; and
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16. A machine-readable medium having instructions stored thereon for execution by a processor to perform a method operable on a plurality of variables having a predetermined representation, the plurality of variables including a plurality of input-only variables, a plurality of output-only variables, and a plurality of both input-and-output variables, the method comprising:
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generating a model comprising a bottleneck architecture, the model including a top layer of nodes including at least the plurality of input-only variables, at least one middle layer of hidden nodes, and a bottom layer of nodes including the plurality of output-only variables and the plurality of input-and-output variables;
determining at least one cluster Corn the model as a predetermined partition of states of the hidden nodes of the at least one middle layer; and
,generating a solution to the model. - View Dependent Claims (17, 18, 19, 20, 21, 22, 23)
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24. A machine-readable medium having instructions stored thereon for execution by a processor to perform a method operable on a plurality of variables having a predetermined representation, the plurality of variables including a plurality of input-only variables, a plurality of output-only variables, and a plurality of both input-and-output variables, the method comprising:
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generating a model comprising a bottleneck architecture, the model including a top layer of nodes including at least the plurality of input-only variables, at least one middle layer of hidden nodes, and a bottom layer of nodes including the plurality of output-only variables and the plurality of input-and-output variables;
determining at least one cluster from the model;
generating a solution to the model; and
,displaying a visualization of the at least one cluster. - View Dependent Claims (25, 26, 27, 28, 29)
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30. A computer-implemented method for generating a model from which at least one cluster can be determined there from and operable on a plurality of variables having a predetermined representation, the plurality of variables including a plurality of input-only variables, a plurality of output-only variables, and a plurality of both input-and-output variables, the method comprising:
generating a model comprising a bottleneck architecture, the model including a top layer of nodes including at least the plurality of input-only variables, at least one middle layer of discrete hidden nodes, and a bottom layer of nodes including the plurality of output-only variables and the plurality of input-and-output variables. - View Dependent Claims (31, 32, 33, 34)
Specification