ParaKMeans: Implementation of a parallelized K-means algorithm suitable for general laboratory use.
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AutoClass@IJM: a powerful tool for Bayesian classification of heterogeneous data in biology.A highly efficient multi-core algorithm for clustering extremely large datasets.ParaSAM: a parallelized version of the significance analysis of microarrays algorithmAn Efficient Computational Framework for the Analysis of Whole Slide Images: Application to Follicular Lymphoma ImmunohistochemistryA modified hyperplane clustering algorithm allows for efficient and accurate clustering of extremely large datasets.A roadmap of clustering algorithms: finding a match for a biomedical application.An Efficient MapReduce-Based Parallel Clustering Algorithm for Distributed Traffic Subarea Division
P2860
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P2860
ParaKMeans: Implementation of a parallelized K-means algorithm suitable for general laboratory use.
description
2008 nî lūn-bûn
@nan
2008 թուականի Ապրիլին հրատարակուած գիտական յօդուած
@hyw
2008 թվականի ապրիլին հրատարակված գիտական հոդված
@hy
2008年の論文
@ja
2008年論文
@yue
2008年論文
@zh-hant
2008年論文
@zh-hk
2008年論文
@zh-mo
2008年論文
@zh-tw
2008年论文
@wuu
name
ParaKMeans: Implementation of ...... le for general laboratory use.
@ast
ParaKMeans: Implementation of ...... le for general laboratory use.
@en
ParaKMeans: Implementation of ...... le for general laboratory use.
@nl
type
label
ParaKMeans: Implementation of ...... le for general laboratory use.
@ast
ParaKMeans: Implementation of ...... le for general laboratory use.
@en
ParaKMeans: Implementation of ...... le for general laboratory use.
@nl
prefLabel
ParaKMeans: Implementation of ...... le for general laboratory use.
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ParaKMeans: Implementation of ...... le for general laboratory use.
@en
ParaKMeans: Implementation of ...... le for general laboratory use.
@nl
P2093
P2860
P356
P1433
P1476
ParaKMeans: Implementation of ...... le for general laboratory use.
@en
P2093
Nikhil Garge
Piotr Kraj
Robert Podolsky
P2860
P2888
P356
10.1186/1471-2105-9-200
P577
2008-04-16T00:00:00Z