PREDICT FROM LIBRARY MATHMODEL¶
Loads a saved math model from the d3VIEW model library and runs inference on a supplied dataset, returning predictions and associated metadata. Use this worker when you want to apply a previously trained and stored ML model to new input data without retraining.
When to use¶
Tagged: inference, library, lucy, mathmodel, ml, predict, prediction.
Inputs¶
| Label | ID | Type | Default | Required | Description |
|---|---|---|---|---|---|
| Mathmodel | mathmodel_id | remote_lookup | — | Remote lookup reference to the saved math model in the d3VIEW library; select the target model whose serialized file will be loaded for inference. | |
| Dataset | dataset | dataset | — | ✓ | Tabular input dataset containing the feature columns required by the selected model; schema is validated against the chosen math model — all required feature columns must be present. |
Outputs¶
| Label | ID | Type | Description |
|---|---|---|---|
| Mathmodel | mathmodel_id | integer | Integer identifier of the math model that was used for prediction, passed through for traceability and downstream wiring. |
| LUCY JSON | lucy_json | json | Raw LUCY ML JSON envelope returned by the inference engine, containing full response payload including stdout, metadata, and per-item results. |
| Meta Info | meta_info | dataset | Dataset summarising run-level metadata (e.g., model name, version, prediction timestamp) produced by the LUCY wrapper. |
| Predicted Dataset | dataset | dataset | Output dataset of predicted values keyed by the original row IDs from the input dataset; each row corresponds to one input observation with its model-generated prediction appended. |
Disciplines¶
- ai_ml.model_selection
- ai_ml.supervised.classification
- ai_ml.supervised.regression
- ai_ml.surrogate
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