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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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| Hlavní autoři: | , , |
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| Médium: | Artigo |
| Jazyk: | Inglês |
| Vydáno: |
2004
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| Témata: | |
| On-line přístup: | https://ncbi.nlm.nih.gov/pmc/articles/PMC2846376/ https://ncbi.nlm.nih.gov/pubmed/20351798 |
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