Description Usage Arguments Value See Also

This function uses the `get_avg_activity_diff_based_on_specific_synergy_prediction`

function on a vector of drug combinations that were observed as synergistic
(e.g. by experiments) but also found as such by at least one of the models
(these drug combinations are the `predicted.synergies`

).

1 2 3 4 5 6 | ```
get_avg_activity_diff_mat_based_on_specific_synergy_prediction(
model.predictions,
models.stable.state,
predicted.synergies,
penalty = 0
)
``` |

`model.predictions` |
a |

`models.stable.state` |
a |

`predicted.synergies` |
a character vector of the synergies (drug
combination names) that were predicted by |

`penalty` |
value between 0 and 1 (inclusive). A value of 0 means no penalty and a value of 1 is the strickest possible penalty. Default value is 0. This penalty is used as part of a weighted term to the difference in a value of interest (e.g. activity or link operator difference) between two group of models, to account for the difference in the number of models from each respective model group. |

a matrix whose rows are **vectors of
average node activity state differences** between two groups of models where
the classification for each individual row was based on the prediction or not
of a specific synergistic drug combination.
The row names are the predicted synergies, one per row, while the columns
represent the network's node names. Values are in the [-1,1] interval.

Other average data difference functions:
`get_avg_activity_diff_based_on_mcc_clustering()`

,
`get_avg_activity_diff_based_on_specific_synergy_prediction()`

,
`get_avg_activity_diff_based_on_synergy_set_cmp()`

,
`get_avg_activity_diff_based_on_tp_predictions()`

,
`get_avg_activity_diff_mat_based_on_mcc_clustering()`

,
`get_avg_activity_diff_mat_based_on_tp_predictions()`

,
`get_avg_link_operator_diff_based_on_synergy_set_cmp()`

,
`get_avg_link_operator_diff_mat_based_on_mcc_clustering()`

,
`get_avg_link_operator_diff_mat_based_on_specific_synergy_prediction()`

,
`get_avg_link_operator_diff_mat_based_on_tp_predictions()`

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