DATASET ANALYZE ROBUSTNESS¶
Analyzes the robustness of a dataset by evaluating how stable the relationship between input features and target variables is across the data. Use this worker to assess whether a dataset is reliable and well-conditioned before model training or design-exploration studies.
When to use¶
Classification: process.
Tagged: data_quality, dataset, eda, feature_analysis, robustness.
Inputs¶
| Label | ID | Type | Default | Required | Description |
|---|---|---|---|---|---|
| Dataset | dataset_1 | dataset | — | ✓ | The tabular dataset to be analyzed; must contain both input feature columns and target columns as named fields. |
| Inputs | inputs | text | — | ✓ | One or more column names from dataset_1 to treat as input (predictor) features for the robustness analysis; select all relevant design or measurement variables. |
| Targets | targets | text | — | ✓ | One or more column names from dataset_1 to treat as response (target) variables whose sensitivity to the inputs will be assessed. |
Outputs¶
| Label | ID | Type | Description |
|---|---|---|---|
| Robustness Analysis | robustness_analysis | dataset | A dataset containing the computed robustness metrics (e.g., stability scores, variance contributions) for each input–target combination, suitable for downstream reporting or decision-making. |
Disciplines¶
- ai_ml.preprocessing
- ai_ml.prognosis
- data.statistics
Runnable example¶
A runnable example is registered for this worker. Open the example workflow on the d3VIEW canvas: /api/workflow/example?id=dataset_analyze_robustness
Auto-generated from transformation schema. Worker id: dataset_analyze_robustness. Schema hash: 9e70020657ea. Hand-curated docs in workerexamples/ override this page when present.