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BMCBI
2007
178views more  BMCBI 2007»
15 years 4 months ago
SVM clustering
Background: Support Vector Machines (SVMs) provide a powerful method for classification (supervised learning). Use of SVMs for clustering (unsupervised learning) is now being cons...
Stephen Winters-Hilt, Sam Merat
HIPC
2009
Springer
15 years 2 months ago
Comparing the performance of clusters, Hadoop, and Active Disks on microarray correlation computations
Abstract--Microarray-based comparative genomic hybridization (aCGH) offers an increasingly fine-grained method for detecting copy number variations in DNA. These copy number variat...
Jeffrey A. Delmerico, Nathanial A. Byrnes, Andrew ...
KDD
2003
ACM
122views Data Mining» more  KDD 2003»
16 years 4 months ago
Discovery of climate indices using clustering
To analyze the effect of the oceans and atmosphere on land climate, Earth Scientists have developed climate indices, which are time series that summarize the behavior of selected ...
Michael Steinbach, Pang-Ning Tan, Vipin Kumar, Ste...
IPPS
2000
IEEE
15 years 8 months ago
Reduction Optimization in Heterogeneous Cluster Environments
Network of workstation (NOW) is a cost-effective alternative to massively parallel supercomputers. As commercially available off-the-shelf processors become cheaper and faster, ...
Pangfeng Liu, Da-Wei Wang
BMCBI
2010
151views more  BMCBI 2010»
15 years 4 months ago
Data reduction for spectral clustering to analyze high throughput flow cytometry data
Background: Recent biological discoveries have shown that clustering large datasets is essential for better understanding biology in many areas. Spectral clustering in particular ...
Habil Zare, Parisa Shooshtari, Arvind Gupta, Ryan ...