FIT A LINEAR REGRESSION

Fits a polynomial regression of selectable order (1–5) to an input curve and returns the smoothed best-fit curve. Use this worker to remove noise, extract trends, or produce a clean analytical approximation of any XY curve.

When to use

Classification: process.

Tagged: curve_fitting, linear_regression, polynomial_fit, regression, smoothing, trend.

Inputs

Label ID Type Default Required Description
Reference Curve curvetobeuseasreference vector   The XY curve to fit; provide as a two-column vector (x, y). This is the only data source the regression operates on.
Order order select 1   Polynomial degree for the regression (1 = linear, 2 = quadratic, … 5 = quintic); defaults to 1 (linear). Higher orders capture more curvature but may overfit sparse data.
Number of digitized Points digitize scalar -1   Number of evenly-spaced points used to re-sample the fitted curve before output; set to -1 (default) to keep the same point spacing as the input curve.

Outputs

Label ID Type Description
Fitted Curve curve_linear_fit vector The regression-fitted XY curve evaluated at the original (or re-sampled) x-coordinates, returned as a two-column vector matching the input domain.

Disciplines

  • ai_ml.supervised.regression
  • 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=curve_linear_regression


Auto-generated from transformation schema. Worker id: curve_linear_regression. Schema hash: 4137b148a3ee. Hand-curated docs in workerexamples/ override this page when present.