Datasets › Wine
Wine (Wine Data Set)
These data are the results of a chemical analysis of wines grown in the same region in Italy but derived from three different cultivars. The analysis determined the quantities of 13 constituents found in each of the three types of wines.
Source: UCI Machine Learning Repository Wine Dataset Image Source: https://archive.ics.uci.edu/ml/datasets/Wine
Benchmarks archive 2025-07-28
All 6 leaderboards whose dataset resolves to this page shown (sort by any header). "First row" is the archive's own first row at snapshot, in the archive's row order; nothing here re-ranks and metric direction is not asserted.
| First row (archive order) | Paper | Code | ||||
|---|---|---|---|---|---|---|
| Incremental Constrained Clustering | Wine | MPCK-Means+NPU AUBC-ARI (quality) 0.893±0.016 | Incremental Constrained Clustering by Minimal Weighted... | aymericb213/IAC | 8 | Compare |
| Feature Importance | Wine | Garson Variable Importance Pearson Correlation 0.74 | Variance-Based Feature Importance in Neural Networks | rebelosa/feature-importance-neural-networks | 2 | Compare |
| AutoML | Wine | Logistic Regression accuracy 98.33 | OptiMindTune: A Multi-Agent Framework for Intelligent... | MeherBhaskar/OptiMindTune | 1 | Compare |
| General Classification | Wine | MONT3 Accuracy 100 | Multi-Objective Optimisation of Multi-Output Neural Trees | vojha-code/multi-output-neural-tree | 1 | Compare |
| Graph Classification | Wine | sKNN-LDS Accuracy 98 | Mutual Information Maximization in Graph Neural Networks | CODE-SUBMIT/Graph_Neighborhood_1 +1 | 1 | Compare |
| Image/Document Clustering | Wine | ELSC Accuracy (%) 75.8 | Ensemble Learning for Spectral Clustering | Li-Hongmin/MyPaperWithCode | 1 | Compare |
Papers archive 2025-07-28
6 shown of 6 papers with a leaderboard row on this dataset's benchmarks, newest first. The archive's own "papers using this dataset" list was never published, so this is the benchmark-backed subset; the archive's count for this dataset is 11. The Syntology column is from Syntology's graph (read 2026-09-24), stated per sample; it is not part of any archive number.
| Date | Samples run Syntology | |||
|---|---|---|---|---|
| OptiMindTune: A Multi-Agent Framework for Intelligent Hyperparameter Optimization | 1 | 1 | 25 May 2025 | not harvested |
| Incremental Constrained Clustering by Minimal Weighted Modification | 1 | 8 | 22 Sep 2023 | not harvested |
| Ensemble Learning for Spectral Clustering | 1 | 1 | 20 Nov 2020 | not harvested |
| Multi-Objective Optimisation of Multi-Output Neural Trees | 1 | 1 | 9 Oct 2020 | not harvested |
| Variance-Based Feature Importance in Neural Networks | 1 | 2 | 16 Oct 2019 | not harvested |
| Mutual Information Maximization in Graph Neural Networks | 2 | 1 | 21 May 2019 | not harvested |
Dataset loaders archive 2025-07-28
No loader listed in the archive.
Tasks archive 2025-07-28
License archive 2025-07-28
No licence recorded in the archive. Absence here is not a statement about the dataset's terms.
Modalities archive 2025-07-28
Languages archive 2025-07-28
No language tagged.
Variants archive 2025-07-28
- Wine
1 variant name, as the archive lists them.
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