Partial likelihood of the Cox regression model (proportional hazards). This class gives first order information (gradient and loss) for this model.
features : numpy.ndarray, shape=(n_samples, n_features), (read-only)
The features matrix
times : numpy.ndarray, shape = (n_samples,), (read-only)
Obverved times
censoring : numpy.ndarray, shape = (n_samples,), (read-only)
Boolean indicator of censoring of each sample.
Truemeans true failure, namely non-censored time
n_samples : int (read-only)
Number of samples
n_features : int (read-only)
Number of features
n_failures : int (read-only)
Number of true failure times
n_coeffs : int (read-only)
Total number of coefficients of the model
censoring_rate : float
The censoring_rate (percentage of ???)
Notes
There is no intercept in this model