get_predictions {ICBioMark} | R Documentation |
Produce Predictions on an Unseen Dataset
Description
A function taking a predictive model(s) and new observations, and applying the predictive model to them to return predicted biomarker values.
Usage
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. |
Value
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)