L2CVProfile

This is a function for evaluating model performance on a validation dataset for a range of L2 parameters. It returns: likelihoods, a list of the score (log likelihood or C-index) for each fold; L2_reg_params, the log L2 parameters tested and mean_cvpl, the mean log likelihood for each L2 parameter tested.

Parameters:

• x_train - training set matrix. Expected numpy array.
• ytime_train - time of death or censoring for each patient
• ystatus_train - censoring of each patient
• x_train - validation set matrix. Expected numpy array.
• ytime_train - time of death or censoring for each patient on validation set
• ystatus_train - censoring of each patient on validation set
• model_params = {} - model parameters, see trainCoxMlp
• search_params = {} - model search/training parameters, see trainCoxMlp
• cv_params - validation parameters, see below.
• verbose=True - print more stuff.

cv_params is a dictionary of parameters for validation. It has the following parameters:

• cv_metric - Performance metric for evaluating validation set performance. loglikelihood or cindex. Default is loglikelihood.
• L2_range - List of(log) L2 parameters to cross-validate.