Abstract
The Ambiguity measure is based on a probability distribution derived from a body of evidence using pignistic techniques. The Aggregate Uncertainty measure also creates a probability distribution from a body of evidence but this distribution is chosen to maximize the Shannon entropy. A body of evedince can be used to form a partition of the underlying domain. When we can group the terms of the Abiguity or Aggregate Uncertainty using this partition, some interesting connections between entropies and nonspecificities are revealed.
| Original language | English |
|---|---|
| Title of host publication | 2008 Annual Meeting of the North American Fuzzy Information Processing Society, NAFIPS 2008 |
| DOIs | |
| State | Published - 2008 |
| Event | 2008 Annual Meeting of the North American Fuzzy Information Processing Society, NAFIPS 2008 - New York City, NY, United States Duration: May 19 2008 → May 22 2008 |
Other
| Other | 2008 Annual Meeting of the North American Fuzzy Information Processing Society, NAFIPS 2008 |
|---|---|
| Country | United States |
| City | New York City, NY |
| Period | 5/19/08 → 5/22/08 |
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All Science Journal Classification (ASJC) codes
- Computer Science(all)
- Media Technology
Cite this
Partitions and pignistic distributions in GIT. / Wierman, Mark J.
2008 Annual Meeting of the North American Fuzzy Information Processing Society, NAFIPS 2008. 2008. 4531316.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Partitions and pignistic distributions in GIT
AU - Wierman, Mark J.
PY - 2008
Y1 - 2008
N2 - The Ambiguity measure is based on a probability distribution derived from a body of evidence using pignistic techniques. The Aggregate Uncertainty measure also creates a probability distribution from a body of evidence but this distribution is chosen to maximize the Shannon entropy. A body of evedince can be used to form a partition of the underlying domain. When we can group the terms of the Abiguity or Aggregate Uncertainty using this partition, some interesting connections between entropies and nonspecificities are revealed.
AB - The Ambiguity measure is based on a probability distribution derived from a body of evidence using pignistic techniques. The Aggregate Uncertainty measure also creates a probability distribution from a body of evidence but this distribution is chosen to maximize the Shannon entropy. A body of evedince can be used to form a partition of the underlying domain. When we can group the terms of the Abiguity or Aggregate Uncertainty using this partition, some interesting connections between entropies and nonspecificities are revealed.
UR - http://www.scopus.com/inward/record.url?scp=51149102058&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=51149102058&partnerID=8YFLogxK
U2 - 10.1109/NAFIPS.2008.4531316
DO - 10.1109/NAFIPS.2008.4531316
M3 - Conference contribution
AN - SCOPUS:51149102058
SN - 9781424423521
BT - 2008 Annual Meeting of the North American Fuzzy Information Processing Society, NAFIPS 2008
ER -