get_K | R Documentation |
An internal function, producing the correct bias penalisation for use in predictive model fitting.
get_K(
gen_model,
p_norm,
training_matrix,
marker_training_values = NULL,
method = max
)
gen_model |
(list) A generative mutation model, fitted by fit_gen_model(). |
p_norm |
(numeric) Scaling factor between coefficients of p and parameters of generative model (see paper for details). |
training_matrix |
(sparse matrix) A sparse matrix of mutations in the training dataset, produced by get_mutation_tables(). |
marker_training_values |
(dataframe) A dataframe containing training values for the biomarker in question. |
method |
(function) How to select a representative biomarker value from the training dataset. Defaults to max(). |
A numerical value, to be used as a penalty weighting in the subsequent group lasso optimisation.
K <- get_K(example_gen_model, 1, example_tables$train$matrix)
print(K)
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