.. _auto_dataset_analyze_robustness: *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 ------ .. list-table:: :header-rows: 1 :widths: 20 20 20 20 20 20 * - 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 ------- .. list-table:: :header-rows: 1 :widths: 20 20 20 20 * - 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 `_ .. raw:: html

Auto-generated from transformation schema. Worker id: dataset_analyze_robustness. Schema hash: 9e70020657ea. Hand-curated docs in workerexamples/ override this page when present.