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JMLR
2010
130views more  JMLR 2010»
15 years 1 months ago
MOA: Massive Online Analysis, a Framework for Stream Classification and Clustering
Massive Online Analysis (MOA) is a software environment for implementing algorithms and running experiments for online learning from evolving data streams. MOA is designed to deal...
Albert Bifet, Geoff Holmes, Bernhard Pfahringer, P...
BMCBI
2007
123views more  BMCBI 2007»
15 years 6 months ago
Robust clustering in high dimensional data using statistical depths
Background: Mean-based clustering algorithms such as bisecting k-means generally lack robustness. Although componentwise median is a more robust alternative, it can be a poor cent...
Yuanyuan Ding, Xin Dang, Hanxiang Peng, Dawn Wilki...
CVPR
2006
IEEE
16 years 8 months ago
Spectral Methods for Automatic Multiscale Data Clustering
Spectral clustering is a simple yet powerful method for finding structure in data using spectral properties of an associated pairwise similarity matrix. This paper provides new in...
Arik Azran, Zoubin Ghahramani
ICDM
2008
IEEE
122views Data Mining» more  ICDM 2008»
16 years 1 months ago
Nonnegative Matrix Factorization for Combinatorial Optimization: Spectral Clustering, Graph Matching, and Clique Finding
Nonnegative matrix factorization (NMF) is a versatile model for data clustering. In this paper, we propose several NMF inspired algorithms to solve different data mining problems....
Chris H. Q. Ding, Tao Li, Michael I. Jordan
CEC
2005
IEEE
16 years 6 days ago
Adaptive cluster covering and evolutionary approach: comparison, differences and similarities
In case the objective function to be minimized is not known analytically and no assumption can be made about the single extremum, global optimization (GO) methods must be used. Pap...
Dimitri P. Solomatine