A Framework for Learning from Distributed Data Using Sufficient Statistics and Its Application to Learning Decision Trees
International Journal of Hybrid Intelligent SystemsPublished 1 April 2004
CarageaDoina, SilvescuAdrian, HonavarVasant
Citations2
SJR quartileQ3
SJR score0.35
SNIP0.54
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Abstract
This paper motivates and precisely formulates the problem of learning from distributed data; describes a general strategy for transforming traditional machine learning algorithms into algorithms fo...
Keywords
Computer Science