Hendrik/xgboost
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

[doc] Display survival demos in sphinx doc. [skip ci] (#8328)

Browse Source
This commit is contained in:
Jiaming Yuan
2022-10-13 20:51:23 +08:00
committed by GitHub
parent 3ef1703553
commit 4633b476e9
8 changed files with 31 additions and 15 deletions
Download Patch File Download Diff File Expand all files Collapse all files

6
doc/tutorials/aft_survival_analysis.rst
View File

@@ -98,7 +98,7 @@ Collect the lower bound numbers in one array (let's call it ``y_lower_bound``) a
# 4-by-2 Data matrix
X = np.array([[1, -1], [-1, 1], [0, 1], [1, 0]])
dtrain = xgb.DMatrix(X)
# Associate ranged labels with the data matrix.
# This example shows each kind of censored labels.
# uncensored right left interval
@@ -109,7 +109,7 @@ Collect the lower bound numbers in one array (let's call it ``y_lower_bound``) a
.. code-block:: r
:caption: R
library(xgboost)
# 4-by-2 Data matrix
@@ -165,4 +165,4 @@ Currently, you can choose from three probability distributions for ``aft_loss_di
``extreme`` :math:`e^z e^{-\exp{z}}`
========================= ===========================================
Note that it is not yet possible to set the ranged label using the scikit-learn interface (e.g. :class:`xgboost.XGBRegressor`). For now, you should use :class:`xgboost.train` with :class:`xgboost.DMatrix`.
Note that it is not yet possible to set the ranged label using the scikit-learn interface (e.g. :class:`xgboost.XGBRegressor`). For now, you should use :class:`xgboost.train` with :class:`xgboost.DMatrix`. For a collection of Python examples, see :doc:`/python/survival-examples/index`