[SPARK-34093][ML] param maxDepth should check upper bound
### What changes were proposed in this pull request? update the ParamValidators of `maxDepth` ### Why are the changes needed? current impl of tree models only support maxDepth<=30 ### Does this PR introduce _any_ user-facing change? If `maxDepth`>30, fail quickly ### How was this patch tested? existing testsuites Closes #31163 from zhengruifeng/param_maxDepth_upbound. Authored-by: Ruifeng Zheng <ruifengz@foxmail.com> Signed-off-by: Sean Owen <srowen@gmail.com>
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@ -60,8 +60,9 @@ private[ml] trait DecisionTreeParams extends PredictorParams
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*/
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final val maxDepth: IntParam =
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new IntParam(this, "maxDepth", "Maximum depth of the tree. (Nonnegative)" +
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" E.g., depth 0 means 1 leaf node; depth 1 means 1 internal node + 2 leaf nodes.",
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ParamValidators.gtEq(0))
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" E.g., depth 0 means 1 leaf node; depth 1 means 1 internal node + 2 leaf nodes." +
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" Must be in range [0, 30].",
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ParamValidators.inRange(0, 30))
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/**
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* Maximum number of bins used for discretizing continuous features and for choosing how to split
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@ -67,7 +67,8 @@ class _DecisionTreeParams(HasCheckpointInterval, HasSeed, HasWeightCol):
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typeConverter=TypeConverters.toString)
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maxDepth = Param(Params._dummy(), "maxDepth", "Maximum depth of the tree. (>= 0) E.g., " +
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"depth 0 means 1 leaf node; depth 1 means 1 internal node + 2 leaf nodes.",
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"depth 0 means 1 leaf node; depth 1 means 1 internal node + 2 leaf nodes. " +
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"Must be in range [0, 30].",
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typeConverter=TypeConverters.toInt)
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maxBins = Param(Params._dummy(), "maxBins", "Max number of bins for discretizing continuous " +
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