Dependency network based model (or pattern)

Details Dependency network based model (or pattern) Dependency network based model (or pattern)

2006-01-03

2010-11-09

Fleurantin, Jean B. (Department: 2162)

Data processing: database and file management or data structures

Database design

Data structure types

C707S797000

Reexamination Certificate

active

07831627

ABSTRACT:
A dependency network is created from a training data set utilizing a scalable method. A statistical model (or pattern), such as for example a Bayesian network, is then constructed to allow more convenient inferencing. The model (or pattern) is employed in lieu of the training data set for data access. The computational complexity of the method that produces the model (or pattern) is independent of the size of the original data set. The dependency network directly returns explicitly encoded data in the conditional probability distributions of the dependency network. Non-explicitly encoded data is generated via Gibbs sampling, approximated, or ignored.

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