Automatic Baseline Correction Method Selection

step_measure_baseline_auto() creates a specification of a recipe step that automatically selects and applies the best baseline correction method based on signal characteristics.

Usage

step_measure_baseline_auto(
  recipe,
  measures = NULL,
  methods = c("rolling", "airpls", "snip", "tophat", "minima"),
  role = NA,
  trained = FALSE,
  selected_method = NULL,
  skip = FALSE,
  id = recipes::rand_id("measure_baseline_auto")
)

Arguments

recipe

A recipe object.

measures

An optional character vector of measure column names.

methods

Character vector of methods to consider. Default includes all available methods.

role

Not used.

trained

Logical indicating if the step has been trained.

selected_method

The method selected during training (internal).

skip

Logical. Should the step be skipped when baking?

id

Unique step identifier.

Value

An updated recipe with the new step added.

Details

This step analyzes the signal characteristics (noise level, baseline curvature, peak density) during training and selects an appropriate baseline correction method. The selected method is then applied consistently during baking.

Method selection heuristics:

• High noise, smooth baseline: rolling ball

• Complex curvature: airPLS or arPLS

• Sharp peaks: SNIP or top-hat

• Simple baseline: polynomial or minima

See also

Other measure-baseline: step_measure_baseline_airpls(), step_measure_baseline_als(), step_measure_baseline_arpls(), step_measure_baseline_custom(), step_measure_baseline_gpc(), step_measure_baseline_minima(), step_measure_baseline_morph(), step_measure_baseline_poly(), step_measure_baseline_py(), step_measure_baseline_rf(), step_measure_baseline_rolling(), step_measure_baseline_snip(), step_measure_baseline_tophat(), step_measure_detrend()

Examples

library(recipes)

rec <- recipe(water + fat + protein ~ ., data = meats_long) |>
  update_role(id, new_role = "id") |>
  step_measure_input_long(transmittance, location = vars(channel)) |>
  step_measure_baseline_auto() |>
  prep()