How data partitioning strategies and subset size influence the performance of an ensemble?

When dealing with big data, "divide and conquer" is the most commonly used strategy in practice to partition a big dataset into such smaller subsets that each subset can be handled by a computer or a node of cluster or cloud computing systems. However, among many existing partitioning or s...

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Bibliographische Detailangaben

Hauptverfasser:	Farrash, Majed, Wenjia Wang
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	Accuracy Big data ensemble learning partitioning Partitioning algorithms Radiation detectors Round robin subset size Support vector machines Testing Training
Online-Zugang:	Volltext bestellen
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