Finding reproducible cluster partitions for the k-means algorithm
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FogBank: a single cell segmentation across multiple cell lines and image modalitiesPattern Recognition Analysis Reveals Unique Contrast Sensitivity Isocontours Using Static Perimetry Thresholds Across the Visual FieldNetwork-Based Approaches to Explore Complex Biological Systems towards Network Medicine
P2860
Finding reproducible cluster partitions for the k-means algorithm
description
2013 nî lūn-bûn
@nan
2013 թուականի Յունուարին հրատարակուած գիտական յօդուած
@hyw
2013 թվականի հունվարին հրատարակված գիտական հոդված
@hy
2013年の論文
@ja
2013年論文
@yue
2013年論文
@zh-hant
2013年論文
@zh-hk
2013年論文
@zh-mo
2013年論文
@zh-tw
2013年论文
@wuu
name
Finding reproducible cluster partitions for the k-means algorithm
@ast
Finding reproducible cluster partitions for the k-means algorithm
@en
Finding reproducible cluster partitions for the k-means algorithm
@nl
type
label
Finding reproducible cluster partitions for the k-means algorithm
@ast
Finding reproducible cluster partitions for the k-means algorithm
@en
Finding reproducible cluster partitions for the k-means algorithm
@nl
prefLabel
Finding reproducible cluster partitions for the k-means algorithm
@ast
Finding reproducible cluster partitions for the k-means algorithm
@en
Finding reproducible cluster partitions for the k-means algorithm
@nl
P2093
P2860
P1433
P1476
Finding reproducible cluster partitions for the k-means algorithm
@en
P2093
Ian H Jarman
Paulo J G Lisboa
Simon J Chambers
Terence A Etchells
P2860
P2888
P356
10.1186/1471-2105-14-S1-S8
P478
14 Suppl 1
P577
2013-01-14T00:00:00Z
P5875
P6179
1017556718