GET ML TASK CONFIGURATIONS¶
Retrieves the canonical configuration schema for a specified ML task type (e.g., clustering, regression, classification, PCA, or data-cleaning). Use this worker to discover which parameters and options are available before wiring up a downstream ML worker in a workflow.
When to use¶
Tagged: autoclean, classification, clustering, configuration, feature_importance, ml, pca, regression.
Inputs¶
| Label | ID | Type | Default | Required | Description |
|---|---|---|---|---|---|
| ML Task Type | task_type | select | — | ✓ | The ML task type whose configuration schema should be retrieved; select one of the enumerated options (e.g., ‘kmeans’, ‘rfr’, ‘rfc’, ‘run_pca’, ‘autoclean’) — required, no default. |
Outputs¶
| Label | ID | Type | Description |
|---|---|---|---|
| Status | status | string | String indicating whether the configuration retrieval succeeded (e.g., ‘success’ or an error message). |
| Results | results | string | JSON-formatted string containing the full parameter schema and default values specific to the selected ML task type (e.g., available hyperparameters, required column names, normalization flags). |
Disciplines¶
- ai_ml.model_selection
- ai_ml.preprocessing
- ai_ml.prognosis
- ai_ml.supervised.classification
- ai_ml.supervised.regression
- ai_ml.unsupervised.clustering
- ai_ml.unsupervised.dim_reduction
- platform.workflow
Auto-generated from platform schema. Worker id: ml_get_task_configurations. Schema hash: 4f14ec5ed764. Hand-curated docs in workerexamples/ override this page when present.