| Publisher | Intel | ||
|---|---|---|---|
| Format | 132.0KB PDF | Date added | 18 Jul 2005 |
| Topics | Knowledge and Data Management | ||
| Downloads | 45 | ||
Several reasoning tasks need to scale over the volume of evidence and the entities of interest. A technique used by statisticians is to represent a collection of evidence by the sufficient statistics of the data. This reduces the computation burden on the BN model significantly by representing a large set of records (and therefore nodes) with a single node. However, this procedure is not general in terms of data types and model parameters. Similar to the notion of the sufficient statistics, many real world applications of Bayesian Networks use this common pattern of use where a set of evidence is approximated by an aggregate score of the collective.
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