An efficient algorithm for partitioning the range of a continuous variable to a discrete Ε½ . number of intervals, for use in the construction of Bayesian belief networks BBNs , is presented here. The partitioning minimizes the information loss, relative to the number of intervals used to represent t
β¦ LIBER β¦
Continuous process improvement using Bayesian belief networks
β Scribed by Nigel D.C. Lewis
- Publisher
- Elsevier Science
- Year
- 1999
- Tongue
- English
- Weight
- 275 KB
- Volume
- 37
- Category
- Article
- ISSN
- 0360-8352
No coin nor oath required. For personal study only.
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