Consensus-Based Clustering in Numerical Decision-Making
| Autor: | David Pérez-Román, José Luis García-Lapresta |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Theoretical computer science
Computer science Correlation clustering 02 engineering and technology Function (mathematics) 010501 environmental sciences 01 natural sciences Measure (mathematics) Computer Science::Multiagent Systems Biclustering Similarity (network science) CURE data clustering algorithm 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Cluster analysis 0105 earth and related environmental sciences Unit interval |
| Zdroj: | Advances in Intelligent Systems and Computing ISBN: 9783319429717 SMPS |
| DOI: | 10.1007/978-3-319-42972-4_30 |
| Popis: | In this paper, we consider that a set of agents assess a set of alternatives through numbers in the unit interval. In this setting, we introduce a measure that assigns a degree of consensus to each subset of agents with respect to every subset of alternatives. This consensus measure is defined as 1 minus the outcome generated by a symmetric aggregation function to the distances between the corresponding individual assessments. We establish some properties of the consensus measure, some of them depending on the used aggregation function. We also introduce an agglomerative hierarchical clustering procedure that is generated by similarity functions based on the previous consensus measures. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|