Cindex
Introduction
The concordance index or Cindex is a generalization of the area under the ROC curve (AUC) that can take into account censored data. It represents the global assessment of the model discrimination power: this is the model’s ability to correctly provide a reliable ranking of the survival times based on the individual risk scores. It can be computed with the following formula:
with:
 , the risk score of a unit
 if else
 if else
Similarly to the AUC, corresponds to the best model prediction, and represents a random prediction.
Location
The function can be found at pysurvival.utils.metrics.concordance_index
.
API
concordance_index
 Concordance Index computations
concordance_index(model, X, T, E, include_ties = True, additional_results=False)
Parameters:

model
: Pysurvival object  Pysurvival model 
X
: arraylike  input samples; where the rows correspond to an individual sample and the columns represent the features (shape=[n_samples, n_features]). 
T
: arraylike  target values describing the time when the event of interest or censoring occurred. 
E
: arraylike  values that indicate if the event of interest occurred i.e.: E[i]=1 corresponds to an event, and E[i] = 0 means censoring, for all i. 
include_ties
: bool (default=True)  Specifies whether ties in risk score are included in calculations 
additional_results
: bool (default=False)  Specifies whether only the cindex should be returned (False) or if a dict of values should returned. In that case, the values are: c_index
 nb_pairs
 nb_concordant_pairs
Returns:

c_index
: float or dict  Result of the function if
additional_results = False
then c_index is float.  if
additional_results = True
then c_index is dict, such thatc_index = {'c_index': ., 'nb_pairs': ., 'nb_concordant_pairs': .}
 if