Since the given unobserved.model.predictions
data.frame has only the
negative results, this function returns the total number of 0's and
NA's in each row.
calculate_models_synergies_tn(unobserved.model.predictions)
data.frame
object with rows the models
and columns the drug combinations that were found/observed as non-synergistic
(negative results). Possible values for each model-drug combination
element are either 0 (no synergy predicted), 1 (synergy was
predicted) or NA (couldn't find stable states in either the drug
combination inhibited model or in any of the two single-drug inhibited models)
an integer vector with elements the number of true negative predictions
per model. The model names are given in the names attribute (same order
as in the rownames attribute of the unobserved.model.predictions
data.frame
).
Other confusion matrix calculation functions:
calculate_mcc()
,
calculate_models_mcc()
,
calculate_models_synergies_fn()
,
calculate_models_synergies_fp()
,
calculate_models_synergies_tp()