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» An overview of clustering methods
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BMCBI
2008
104views more  BMCBI 2008»
15 years 6 months ago
Missing value imputation improves clustering and interpretation of gene expression microarray data
Background: Missing values frequently pose problems in gene expression microarray experiments as they can hinder downstream analysis of the datasets. While several missing value i...
Johannes Tuikkala, Laura Elo, Olli Nevalainen, Ter...
177
Voted
ICC
2007
IEEE
102views Communications» more  ICC 2007»
16 years 1 months ago
Use of Fuzzy Bayesian Clustering to Enhance Generalization Capacity of Radio Network Planning Tool
— To enhance the generalization capacity of a distribution learning method, we propose to use a fuzzy Bayesian framework based on Bayes rules. The precision of the learning resul...
Zakaria Nouir, Berna Sayraç, Benoît F...
148
Voted
ACIVS
2006
Springer
16 years 21 days ago
Alternative Fuzzy Clustering Algorithms with L1-Norm and Covariance Matrix
In fuzzy clustering, the fuzzy c-means (FCM) algorithm is the best known and most used method. Although FCM is a very useful method, it is sensitive to noise and outliers so that W...
Miin-Shen Yang, Wen-Liang Hung, Tsiung-Iou Chung
PDP
2003
IEEE
15 years 12 months ago
Load Balancing for Spatial-grid-based Parallel Numeric Simulations on Clusters of SMPs
Load distribution is an essential factor to parallel efficiency of numerical simulations that are based on spatial grids, especially on clusters of symmetric multiprocessors (SMPs...
Huaien Gao, Andreas Schmidt, Amitava Gupta, Peter ...
ICASSP
2010
IEEE
15 years 6 months ago
Partial clustering using a time-varying frequency model for singing voice detection
We propose a new method to group partials produced by each instrument of a polyphonic audio mixture. This method works for pitched and harmonic instruments and is specially adapte...
Lise Regnier, Geoffroy Peeters