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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| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 555 | Discovering Denial Constraints | 2013 | VLDB | 0.00020254908 |
| 560 | Dependencies Revisited for Improving Data Quality | 2008 | PODS | 0.00020141923 |
| 3,818 | Embedded Functional Dependencies and Data-completeness Tailored Database Design | 2019 | VLDB | 6.7300958e-05 |
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