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BIBE
2004
IEEE
120views Bioinformatics» more  BIBE 2004»
14 years 2 months ago
Identifying Projected Clusters from Gene Expression Profiles
In microarray gene expression data, clusters may hide in subspaces. Traditional clustering algorithms that make use of similarity measurements in the full input space may fail to ...
Kevin Y. Yip, David W. Cheung, Michael K. Ng, Kei-...
ICMLC
2010
Springer
13 years 8 months ago
An integrity-based fuzzy c-means method resolving cluster size sensitivity problem
: Cluster size insensitive FCM (csiFCM) dynamically adjusts the membership value of each object based on the size of the cluster to which it is assigned after defuzzification to re...
Y. H. Lai, P. W. Huang, P. L. Lin
KES
2005
Springer
14 years 3 months ago
Towards Adaptive Clustering in Self-monitoring Multi-agent Networks
A Decentralised Adaptive Clustering (DAC) algorithm for self-monitoring impact sensing networks is presented within the context of CSIRO-NASA Ageless Aerospace Vehicle project. DAC...
Piraveenan Mahendra rajah, Mikhail Prokopenko, Pet...
AGENTS
2000
Springer
14 years 2 months ago
Unsupervised clustering of robot activities: a Bayesian approach
Our goal is for robots to learn conceptual systems su cient for natural language and planning. The learning should be autonomous, without supervision. The rst steps in building a ...
Marco Ramoni, Paola Sebastiani, Paul R. Cohen
IDA
2007
Springer
14 years 4 months ago
Compact and Understandable Descriptions of Mixtures of Bernoulli Distributions
Abstract. Finite mixture models can be used in estimating complex, unknown probability distributions and also in clustering data. The parameters of the models form a complex repres...
Jaakko Hollmén, Jarkko Tikka