ADESIT: Visualize the Limits of your Data in a Machine Learning Process
Summary: ADESIT evaluates dataset readiness for supervised learning via statistics and visual exploration, using functional dependencies to bound accuracy. Post-selection refinement: cleaning and exporting subsets to reveal regions needing higher precision. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Pierre Faure-Giovagnoli (CNRS; Claude Bernard Lyon 1 University; Compagnie Nationale du Rhone; National Institute of Applied Sciences of Lyon; University of Lyon)
- 2. Marie Le Guilly (CNRS; Claude Bernard Lyon 1 University; National Institute of Applied Sciences of Lyon; University of Lyon)
- 3. Jean-Marc Petit (CNRS; Claude Bernard Lyon 1 University; National Institute of Applied Sciences of Lyon; University of Lyon)
- 4. Vasile-Marian Scuturici (CNRS; Claude Bernard Lyon 1 University; National Institute of Applied Sciences of Lyon; University of Lyon)
BibTeX Citation
@article{fauregiovagnoli_vldb21,
title = {{ADESIT: Visualize the Limits of your Data in a Machine Learning Process}},
author = {Faure-Giovagnoli, Pierre and Le Guilly, Marie and Petit, Jean-Marc and Scuturici, Vasile-Marian},
journal = {PVLDB},
series = {{VLDB} '21},
volume = {14},
number = {12},
pages = {2679--2682},
doi = {10.14778/3476311.3476318},
url = {https://doi.org/10.14778/3476311.3476318},
year = {2021}
}
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Outgoing Citations (Sorted by Pagerank)
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 376 | Discovering Denial Constraints | 2013 | VLDB | 0.00019677674 |
| 494 | Dependencies Revisited for Improving Data Quality | 2008 | PODS | 0.00017526549 |
| 3,609 | Embedded Functional Dependencies and Data-completeness Tailored Database Design | 2019 | VLDB | 7.2602055e-05 |
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