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A Framework for Learning from Distributed Data Using Sufficient Statistics and its Application to Learning Decision Trees

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 for learning from distributed data; demonstrates the application of this strategy to devise algorithms fo...

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Библиографические подробности
Главные авторы: Caragea, Doina, Silvescu, Adrian, Honavar, Vasant
Формат: Artigo
Язык:Inglês
Опубликовано: 2004
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Online-ссылка:https://ncbi.nlm.nih.gov/pmc/articles/PMC2846376/
https://ncbi.nlm.nih.gov/pubmed/20351798
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