Github user BryanCutler commented on a diff in the pull request:
https://github.com/apache/spark/pull/21465#discussion_r239245388
--- Diff: python/pyspark/ml/regression.py ---
@@ -705,12 +710,59 @@ def getNumTrees(self):
return self.getOrDefault(self.numTrees)
-class GBTParams(TreeEnsembleParams):
+class GBTParams(TreeEnsembleParams, HasMaxIter, HasStepSize,
HasValidationIndicatorCol):
"""
Private class to track supported GBT params.
"""
+
+ stepSize = Param(Params._dummy(), "stepSize",
+ "Step size (a.k.a. learning rate) in interval (0, 1]
for shrinking " +
+ "the contribution of each estimator.",
+ typeConverter=TypeConverters.toFloat)
+
+ validationTol = Param(Params._dummy(), "validationTol",
+ "Threshold for stopping early when fit with
validation is used. " +
+ "If the error rate on the validation input
changes by less than the " +
+ "validationTol, then learning will stop early
(before `maxIter`). " +
+ "This parameter is ignored when fit without
validation is used.",
+ typeConverter=TypeConverters.toFloat)
+
+ @since("3.0.0")
+ def setValidationTol(self, value):
+ """
+ Sets the value of :py:attr:`validationTol`.
+ """
+ return self._set(validationTol=value)
+
+ @since("3.0.0")
+ def getValidationTol(self):
+ """
+ Gets the value of validationTol or its default value.
+ """
+ return self.getOrDefault(self.validationTol)
+
+
+class GBTRegressorParams(GBTParams, TreeRegressorParams):
+ """
+ Private class to track supported GBTRegressor params.
+
+ .. versionadded:: 3.0.0
+ """
+
supportedLossTypes = ["squared", "absolute"]
+ lossType = Param(Params._dummy(), "lossType",
+ "Loss function which GBT tries to minimize
(case-insensitive). " +
+ "Supported options: " + ", ".join(supportedLossTypes),
+ typeConverter=TypeConverters.toString)
+
+ @since("1.4.0")
+ def setLossType(self, value):
--- End diff --
`setLossType` should be in the estimator and `getLossType` should be here
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