Sample-data demonstration
This shows our AI testing process on public sample data. You can't upload your own data here.
From YourCloudGroup Model Manager.

Question: Which products will be rated highly
Sample data: Wine Quality (UCI)
Attribution: Cortez, P., Cerdeira, A., Almeida, F., Matos, T., & Reis, J. (2009). Wine Quality [Dataset]. UCI Machine Learning Repository. https://doi.org/10.24432/C56S3T. CC BY 4.0. Modified: split into training and held-out rows, predictions added.
Predicts: good wine: quality 7 or above (yes/no) (Classification)

Result
Its predictive value is WEAK, measured but not clearly better than the baseline.
Certification: CERTIFIED — AUDITABLE & REPEATABLE PREDICTIVE MODEL
Value verified: no. The winning model showed limited improvement over the baseline; production value is not established.
Winner: Random Forest, best of 12 models built
Trained on: 4,409 rows

Certificate figures: the holdout half of the blind rows, 161 rows that took no part in choosing the winner
Balanced-accuracy lift: 31.6% (90% range 18.0-47.0%)
Balanced accuracy: 65.8% vs 50.0% for the baseline
Baseline: always predict the most common training class ('no')

Compare figures: all 322 blind rows, including the half the winner was chosen on
Correct: 276 of 322
Confusion (rows = actual, columns = predicted): actual 0 (no): 0 (no) 252, 1 (yes) 18; actual 1 (yes): 0 (no) 28, 1 (yes) 24
The product marks these Compare figures as diagnostic: "These results do not establish predictive performance" (outcome timing was not declared for this run).

The predictions file
322 held-out rows, one per line: heldout_row, fixed acidity, volatile acidity, citric acid, residual sugar, chlorides, free sulfur dioxide, total sulfur dioxide, density, pH, sulphates, alcohol, actual_good_wine, predicted_good_wine, confidence.
heldout_row numbers the held-out rows 1 to N in the order the product tested them. It is not a row number from the original dataset: the split shuffled the rows.

Run: model 9d7ae76b-5d7e-4f60-8a55-60887bdcf73f, tournament winequality_goodwine_20261028-213111, completed 2026-10-28T21:33:04Z
Dataset file sha256: c6da9a01202ac30010c06d7f470d6315197f4a1818eaf09e47b15a9360aca55d