Github user mengxr commented on a diff in the pull request:
https://github.com/apache/spark/pull/8926#discussion_r40636077
--- Diff: python/pyspark/ml/regression.py ---
@@ -608,6 +609,141 @@ class GBTRegressionModel(TreeEnsembleModels):
.. versionadded:: 1.4.0
"""
+@inherit_doc
+class AFTSurvivalRegression(JavaEstimator, HasFeaturesCol, HasLabelCol,
HasPredictionCol,
+ HasFitIntercept, HasMaxIter, HasTol):
+ """
+ `https://en.wikipedia.org/wiki/Accelerated_failure_time_model`
+ Fit a parametric survival regression model named accelerated failure
time (AFT) model
+ based on the Weibull distribution of the survival time.
+
+ >>> 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")
+ quantileProbabilities = \
+ Param(Params._dummy(), "quantileProbabilities",
+ "quantile probabilities array" +
+ ", array is not empty and every probability is in range
[0,1]")
+ quantilesCol = Param(Params._dummy(), "quantilesCol",
+ "quantiles column name")
+
+ @keyword_only
+ def __init__(self, featuresCol="features", labelCol="label",
predictionCol="prediction",
+ fitIntercept=True, maxIter=100, tol=1E-6,
censorCol="censor",
+ quantileProbabilities=[0.01, 0.05, 0.1, 0.25, 0.5, 0.75,
0.9, 0.95, 0.99],
+ quantilesCol=None):
+ """
+ __init__(self, featuresCol="features", labelCol="label",
predictionCol="prediction",
+ fitIntercept=True, maxIter=100, tol=1E-6,
censorCol="censor",
+ quantileProbabilities=[0.01, 0.05, 0.1, 0.25, 0.5, 0.75,
0.9, 0.95, 0.99],
+ quantilesCol=None):
+ """
+ super(AFTSurvivalRegression, self).__init__()
+ self._java_obj = self._new_java_obj(
+ "org.apache.spark.ml.regression.AFTSurvivalRegression",
self.uid)
+ self.censorCol = \
+ Param(self, "censorCol",
+ "censor column name")
+ self.quantileProbabilities = \
+ Param(self, "quantileProbabilities",
+ "quantile probabilities array" +
+ ", array is not empty and every probability is in range
[0,1]")
+ self.quantilesCol = Param(self, "quantilesCol",
+ "quantiles column name")
+ self._setDefault(censorCol="censor",
+ quantileProbabilities=[0.01, 0.05, 0.1, 0.25,
0.5, 0.75, 0.9, 0.95, 0.99])
+ kwargs = self.__init__._input_kwargs
+ self.setParams(**kwargs)
+
+ @keyword_only
+ @since("1.6.0")
+ def setParams(self, featuresCol="features", labelCol="label",
predictionCol="prediction",
+ fitIntercept=True, maxIter=100, tol=1E-6,
censorCol="censor",
+ quantileProbabilities=[0.01, 0.05, 0.1, 0.25, 0.5, 0.75,
0.9, 0.95, 0.99],
+ quantilesCol=None):
+ """
+ setParams(self, featuresCol="features", labelCol="label",
predictionCol="prediction",
--- End diff --
Same about `\` at the end and the issue with mutable default value.
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