get_predictions function

Produce Predictions on an Unseen Dataset

Produce Predictions on an Unseen Dataset

A function taking a predictive model(s) and new observations, and applying the predictive model to them to return predicted biomarker values.

get_predictions(pred_model, new_data, s = NULL, max_panel_length = NULL)

Arguments

  • pred_model: (list) A predictive model as fitted by pred_first_fit(), pred_refit_panel() or pred_refit_range().
  • new_data: (list) A new dataset, containing a matrix of observations and a list of sample IDs. Likely comes from the 'train', 'val' or 'test' argument of a call to get_mutation_tables().
  • s: (numeric) If producing predictions for a single panel, s chooses which panel (column in a pred_fit object) to produce predictions for.
  • max_panel_length: (numeric) If producing predictions for a single panel, maximum panel length to specify that panel.

Returns

A list with two elements:

  • predictions, a matrix containing a row for each sample and a column for each panel.
  • panel_lengths, a vector containing the length of each panel.

Examples

example_predictions <- get_predictions(example_refit_range, new_data = example_tables$val)
  • Maintainer: Jacob R. Bradley
  • License: MIT + file LICENSE
  • Last published: 2021-11-15

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