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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)

Paper ID
12632
Venue
VLDB
Year
2021
Pagerank
5.093636e-05
Overall Rank
11,707 | 19.68%
DOI
10.14778/3476311.3476318

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Authors

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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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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