SPRINT: A Scalable Parallel Classifier for Data Mining
Summary: SPRINT is an out-of-core decision-tree classifier that eliminates in-memory dataset requirements, enabling scalable mining of large databases. Its partitionable design lets many processors collaboratively build one consistent model with strong parallel scalability. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. John Shafer (IBM; University of Wisconsin)
- 2. Rakesh Agrawal (IBM)
- 3. Manish Mehta (IBM)
BibTeX Citation
@article{shafer_vldb96,
title = {{SPRINT: A Scalable Parallel Classifier for Data Mining}},
author = {Shafer, John and Agrawal, Rakesh and Mehta, Manish},
journal = {PVLDB},
series = {{VLDB} '96},
pages = {544--555},
year = {1996}
}
Incoming Citations (Sorted by Pagerank)
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Outgoing Citations (Sorted by Pagerank)
Showing 1 of 1 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 440 | An Interval Classifier for Database Mining Applications | 1992 | VLDB | 0.00018409145 |
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