Github user vectorijk commented on a diff in the pull request:
https://github.com/apache/spark/pull/8926#discussion_r40882471
--- Diff: python/pyspark/ml/regression.py ---
@@ -609,6 +611,147 @@ class GBTRegressionModel(TreeEnsembleModels):
"""
+@inherit_doc
+class AFTSurvivalRegression(JavaEstimator, HasFeaturesCol, HasLabelCol,
HasPredictionCol,
+ HasFitIntercept, HasMaxIter, HasTol):
+ """
+ Accelerated Failure Time(AFT) Model Survival Regression
+
+ Fit a parametric AFT survival regression model based on the Weibull
distribution
+ of the survival time.
+ see also,
`https://en.wikipedia.org/wiki/Accelerated_failure_time_model`
+
+ >>> from pyspark.mllib.linalg import Vectors
+ >>> df = sqlContext.createDataFrame([
+ ... (1.0, Vectors.dense(1.0), 1.0),
+ ... (0.0, Vectors.sparse(1, [], []), 0.0)], ["label", "features",
"censor"])
+ >>> aftsr = AFTSurvivalRegression()
+ >>> model = aftsr.fit(df)
+ >>> model.transform(df).show()
+ +-----+---------+------+----------+
+ |label| features|censor|prediction|
+ +-----+---------+------+----------+
+ | 1.0| [1.0]| 1.0| 1.0|
+ | 0.0|(1,[],[])| 0.0| 1.0|
+ +-----+---------+------+----------+
+ ...
+
+ .. versionadded:: 1.6.0
+ """
+
+ # a placeholder to make it appear in the generated doc
+ censorCol = Param(Params._dummy(), "censorCol",
+ "censor column name. The value of this column could
be 0 or 1. " +
+ "If the value is 1, it means the event has occurred
i.e. " +
+ "uncensored; otherwise censored.")
+ quantileProbabilities = \
+ Param(Params._dummy(), "quantileProbabilities",
+ "quantile probabilities array. Values of the quantile
probabilities array " +
+ "should be in the range [0, 1] and the array should be
non-empty.")
--- End diff --
changed that in doc
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