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Semi-supervised hierarchical clustering ensemble and its application
- Source :
- Neurocomputing. 173:1362-1376
- Publication Year :
- 2016
- Publisher :
- Elsevier BV, 2016.
-
Abstract
- Clustering ensemble is an important part of ensemble learning. It aims to study and integrate multiple clustering results from different clustering algorithms or same algorithm with different initial parameters for the same dataset. CHAMELEON is a hierarchical clustering algorithm which can discover natural clusters of different shapes and sizes as the result of its merging decision dynamically adapts to the different clustering model characterized. Inspired by the idea of CHAMELEON, the paper proposes a novel clustering ensemble models including semi-supervised method and discusses its application in fault diagnosis of high speed train (HST) running gear. The contributions of this paper include: constructing a sparse graph via the similarity matrix which aggregates multiple clustering results; partitioning the sparse graph (vertex=object, edge weight=similarity) into a large number of relatively small sub-clusters; obtaining the final clustering partition by merging these sub-clusters repeatedly. The experimental results demonstrate that our method outperforms some of state-of-the-art ensemble algorithms regarding the accuracy and stability and recognizes fault patterns of HST running gear effectively.
- Subjects :
- DBSCAN
Clustering high-dimensional data
Fuzzy clustering
Computer science
Cognitive Neuroscience
Correlation clustering
Single-linkage clustering
Conceptual clustering
02 engineering and technology
computer.software_genre
Biclustering
Artificial Intelligence
CURE data clustering algorithm
020204 information systems
Consensus clustering
0202 electrical engineering, electronic engineering, information engineering
Cluster analysis
k-medians clustering
Brown clustering
business.industry
Constrained clustering
Pattern recognition
Ensemble learning
Computer Science Applications
Hierarchical clustering
ComputingMethodologies_PATTERNRECOGNITION
Data stream clustering
Canopy clustering algorithm
FLAME clustering
Affinity propagation
020201 artificial intelligence & image processing
Data mining
Artificial intelligence
Hierarchical clustering of networks
business
computer
Subjects
Details
- ISSN :
- 09252312
- Volume :
- 173
- Database :
- OpenAIRE
- Journal :
- Neurocomputing
- Accession number :
- edsair.doi...........1bc5d9fee2e6ced7cf0ddc4236afb65f