Sciweavers

74 search results - page 4 / 15
» Initialization of Iterative Refinement Clustering Algorithms
Sort
View
ICDM
2010
IEEE
125views Data Mining» more  ICDM 2010»
13 years 5 months ago
Evolving Ensemble-Clustering to a Feedback-Driven Process
Abstract--Data clustering is a highly used knowledge extraction technique and is applied in more and more application domains. Over the last years, a lot of algorithms have been pr...
Martin Hahmann, Dirk Habich, Wolfgang Lehner
CEC
2008
IEEE
14 years 1 months ago
A Quantum-inspired Genetic Algorithm for data clustering
—The conventional K-Means clustering algorithm must know the number of clusters in advance and the clustering result is sensitive to the selection of the initial cluster centroid...
Jing Xiao, YuPing Yan, Ying Lin, Ling Yuan, Jun Zh...
FQAS
2004
Springer
126views Database» more  FQAS 2004»
14 years 25 days ago
Cluster Characterization through a Representativity Measure
Clustering is an unsupervised learning task which provides a decomposition of a dataset into subgroups that summarize the initial base and give information about its structure. We ...
Marie-Jeanne Lesot, Bernadette Bouchon-Meunier
BMVC
2001
13 years 9 months ago
An EM-like Algorithm for Motion Segmentation via Eigendecomposition
This paper presents an iterative maximum likelihood framework for motion segmentation via the pairwise checking of pixel blocks. We commence from a characterisation of the motion ...
Antonio Robles-Kelly, Edwin R. Hancock
CVPR
2008
IEEE
14 years 9 months ago
Generalised blurring mean-shift algorithms for nonparametric clustering
Gaussian blurring mean-shift (GBMS) is a nonparametric clustering algorithm, having a single bandwidth parameter that controls the number of clusters. The algorithm iteratively sh...
Miguel Á. Carreira-Perpiñán