USING PREDICTED VALUES FROM ML, RE-CONSTRUCT A CURVE BY INTERPOLATING FROM CURVES USED IN TRAINING

Given a set of training curves and ML-predicted scalar values, reconstructs a new curve by interpolating across the training curve group at the predicted points. Use this worker to materialise a curve prediction produced by an upstream regression or surrogate model.

When to use

Classification: process.

Tagged: curve_group, curve_reconstruction, interpolation, ml_prediction, surrogate, transformations.

Inputs

Label ID Type Default Required Description
Curve Group curvegroup vector   Collection of training curves (vector/curve-group format) from which the reconstructed curve is interpolated; must contain the curves that were used during ML model training.
prediction_points prediction_points string   JSON-serialised or comma-separated string of ML-predicted scalar values (e.g. feature coordinates) that define the interpolation point within the training curve space; leave empty if not yet available from an upstream model.

Outputs

Label ID Type Description
curves_reconstruct_from_prediction_output_1 curves_reconstruct_from_prediction_output_1 vector Reconstructed curve obtained by interpolating the training curve group at the supplied prediction points; format matches the input curve-group vector type.

Disciplines

  • ai_ml.supervised.regression
  • ai_ml.surrogate
  • data.curve.pair
  • data.curve.transform

Runnable example

A runnable example is registered for this worker. Open the example workflow on the d3VIEW canvas: /api/workflow/example?id=curves_reconstruct_from_prediction


Auto-generated from transformation schema. Worker id: curves_reconstruct_from_prediction. Schema hash: 8f1b94be9764. Hand-curated docs in workerexamples/ override this page when present.