Name
Abstract | ||
|---|---|---|
A partitioning approach to the problem of dealing with the entropy of incomplete information systems is explored. The aim is to keep into account the incompleteness and at the same time to obtain a probabilistic partition of the information system. For the resulting probabilistic partition, measures of entropy and co-entropy are defined, similarly to the entropies and co-entropies defined for the complete case. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1007/978-3-540-72458-2_10 | RSKT |
Keywords | Field | DocType |
partitioning approach,probabilistic partition,information system,incomplete information system,complete case,incomplete information,entropy | Transfer entropy,Computer science,Maximum entropy thermodynamics,Binary entropy function,Joint entropy,Artificial intelligence,Statistical physics,Combinatorics,Pattern recognition,Joint quantum entropy,Information diagram,Conditional entropy,Principle of maximum entropy | Conference |
Volume | ISSN | Citations |
4481 | 0302-9743 | 5 |
PageRank | References | Authors |
0.48 | 9 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Daniela Bianucci | 1 | 80 | 4.30 |
| Gianpiero Cattaneo | 2 | 566 | 58.22 |
| Davide Ciucci | 3 | 672 | 53.74 |