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» Measuring the Quality of Approximated Clusterings
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CIKM
2006
Springer
15 years 3 months ago
Efficiently clustering transactional data with weighted coverage density
In this paper, we propose a fast, memory-efficient, and scalable clustering algorithm for analyzing transactional data. Our approach has three unique features. First, we use the c...
Hua Yan, Keke Chen, Ling Liu
138
Voted
INFFUS
2006
142views more  INFFUS 2006»
15 years 1 months ago
Moderate diversity for better cluster ensembles
Adjusted Rand index is used to measure diversity in cluster ensembles and a diversity measure is subsequently proposed. Although the measure was found to be related to the quality...
Stefan Todorov Hadjitodorov, Ludmila I. Kuncheva, ...
102
Voted
IJHPCN
2008
94views more  IJHPCN 2008»
15 years 1 months ago
Analysing and improving clustering based sampling for microprocessor simulation
: We propose a set of statistical metrics for making a comprehensive, fair, and insightful evaluation of features, clustering algorithms, and distance measures in representative sa...
Yue Luo, Ajay Joshi, Aashish Phansalkar, Lizy Kuri...
BMCBI
2007
130views more  BMCBI 2007»
15 years 2 months ago
Reproducibility of microarray data: a further analysis of microarray quality control (MAQC) data
Background: Many researchers are concerned with the comparability and reliability of microarray gene expression data. Recent completion of the MicroArray Quality Control (MAQC) pr...
James J. Chen, Huey-miin Hsueh, Robert R. Delongch...
JUCS
2008
125views more  JUCS 2008»
15 years 1 months ago
Passive Estimation of Quality of Experience
: Quality of Experience (QoE) is a promising method to take into account the users' needs in designing, monitoring and managing networks. However, there is a challenge in find...
Denis Collange, Jean-Laurent Costeux