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[MINOR][ML] Remove unnecessary default value setting for evaluators.

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## What changes were proposed in this pull request?
Remove unnecessary default value setting for all evaluators, as we have set them in corresponding _HasXXX_ base classes.

## How was this patch tested?
Existing tests.

Author: Yanbo Liang <ybliang8@gmail.com>

Closes #19262 from yanboliang/evaluation.
This commit is contained in:
Yanbo Liang 2017-09-19 22:22:35 +08:00
parent 8319432af6
commit 2f962422a2
1 changed files with 3 additions and 6 deletions
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9
python/pyspark/ml/evaluation.py
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@ -146,8 +146,7 @@ class BinaryClassificationEvaluator(JavaEvaluator, HasLabelCol, HasRawPrediction
super(BinaryClassificationEvaluator, self).__init__()
self._java_obj = self._new_java_obj(
"org.apache.spark.ml.evaluation.BinaryClassificationEvaluator", self.uid)
self._setDefault(rawPredictionCol="rawPrediction", labelCol="label",
metricName="areaUnderROC")
self._setDefault(metricName="areaUnderROC")
kwargs = self._input_kwargs
self._set(**kwargs)
@ -224,8 +223,7 @@ class RegressionEvaluator(JavaEvaluator, HasLabelCol, HasPredictionCol,
super(RegressionEvaluator, self).__init__()
self._java_obj = self._new_java_obj(
"org.apache.spark.ml.evaluation.RegressionEvaluator", self.uid)
self._setDefault(predictionCol="prediction", labelCol="label",
metricName="rmse")
self._setDefault(metricName="rmse")
kwargs = self._input_kwargs
self._set(**kwargs)
@ -297,8 +295,7 @@ class MulticlassClassificationEvaluator(JavaEvaluator, HasLabelCol, HasPredictio
super(MulticlassClassificationEvaluator, self).__init__()
self._java_obj = self._new_java_obj(
"org.apache.spark.ml.evaluation.MulticlassClassificationEvaluator", self.uid)
self._setDefault(predictionCol="prediction", labelCol="label",
metricName="f1")
self._setDefault(metricName="f1")
kwargs = self._input_kwargs
self._set(**kwargs)