<jupyter_start><jupyter_text>Cox Mixture<jupyter_code>hypers = {
        'use_posteriors': False,
        'model': 'cox_mixture',
        'epochs': 50
            }
results = deep_cox_mixture.experiment(dataset='FLCHAIN', prot_att='sex', groups=(1.0, 0.0), hyperparams=hypers)
deep_cox_mixture.display_results(results)<jupyter_output>--------------------------------------------
Event Horizon: 903.25
--------------------------------------------
          |           Groups               |
--------------------------------------------
Metric    |     1.0  |     0.0  |     all  |
--------------------------------------------

AuC       | 0.78621  | 0.80686  | 0.79624  |
Ctd       | 0.77434  | 0.79639  | 0.78528  |
BrS       | 0.06428  | 0.06123  |  0.0626  |
ECE       | 0.02622  | 0.02998  | 0.02583  |
--------------------------------------------

--------------------------------------------
Event Horizon: 2085.0
--------------------------------------------
          |           Groups               |
--------------------------------------------
Metric    |     1.0  |     0.0  |     all  |
--------------------------------------------

AuC       | 0.79642  | 0.80058  | 0.79768  |
Ctd       | 0.77425  | 0.78108  |  0.7771  |
BrS       | 0.10991  | 0.10802  | 0.10886  |
ECE       | 0.05185  | 0.05411  | 0.04969  |
--------[...]<jupyter_text>Deep Cox Mixture<jupyter_code>hypers = {'use_posteriors': Falase}
deep_cox_mixture.experiment(dataset='SUPPORT', prot_att='race', groups=('white', 'black'), hyperparams=hypers)<jupyter_output>0%|          | 0/50 [00:00<?, ?it/s]
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