From d385cc64e2f9fd8efce90d5d31ce6091945a7a1c Mon Sep 17 00:00:00 2001 From: Rong Ou Date: Wed, 29 Mar 2023 19:13:23 -0700 Subject: [PATCH] Fix aft_loss_distribution documentation (#8995) --- doc/parameter.rst | 6 +++++- 1 file changed, 5 insertions(+), 1 deletion(-) diff --git a/doc/parameter.rst b/doc/parameter.rst index 1e703dacd..e26ec83b2 100644 --- a/doc/parameter.rst +++ b/doc/parameter.rst @@ -372,7 +372,6 @@ Specify the learning task and the corresponding learning objective. The objectiv Note that predictions are returned on the hazard ratio scale (i.e., as HR = exp(marginal_prediction) in the proportional hazard function ``h(t) = h0(t) * HR``). - ``survival:aft``: Accelerated failure time model for censored survival time data. See :doc:`/tutorials/aft_survival_analysis` for details. - - ``aft_loss_distribution``: Probability Density Function used by ``survival:aft`` objective and ``aft-nloglik`` metric. - ``multi:softmax``: set XGBoost to do multiclass classification using the softmax objective, you also need to set num_class(number of classes) - ``multi:softprob``: same as softmax, but output a vector of ``ndata * nclass``, which can be further reshaped to ``ndata * nclass`` matrix. The result contains predicted probability of each data point belonging to each class. - ``rank:pairwise``: Use LambdaMART to perform pairwise ranking where the pairwise loss is minimized @@ -468,6 +467,11 @@ Parameter for using Quantile Loss (``reg:quantileerror``) * ``quantile_alpha``: A scala or a list of targeted quantiles. +Parameter for using AFT Survival Loss (``survival:aft``) and Negative Log Likelihood of AFT metric (``aft-nloglik``) +==================================================================================================================== + +* ``aft_loss_distribution``: Probability Density Function, ``normal``, ``logistic``, or ``extreme``. + *********************** Command Line Parameters ***********************