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Posted to commits@spark.apache.org by jk...@apache.org on 2015/07/31 08:02:19 UTC
spark git commit: [SPARK-7690] [ML] Multiclass classification
Evaluator
Repository: spark
Updated Branches:
refs/heads/master 83670fc9e -> 4e5919bfb
[SPARK-7690] [ML] Multiclass classification Evaluator
Multiclass Classification Evaluator for ML Pipelines. F1 score, precision, recall, weighted precision and weighted recall are supported as available metrics.
Author: Ram Sriharsha <rs...@hw11853.local>
Closes #7475 from harsha2010/SPARK-7690 and squashes the following commits:
9bf4ec7 [Ram Sriharsha] fix indentation
3f09a85 [Ram Sriharsha] cleanup doc
16115ae [Ram Sriharsha] code review fixes
032d2a3 [Ram Sriharsha] fix test
eec9865 [Ram Sriharsha] Fix Python Indentation
1dbeffd [Ram Sriharsha] Merge branch 'master' into SPARK-7690
68cea85 [Ram Sriharsha] Merge branch 'master' into SPARK-7690
54c03de [Ram Sriharsha] [SPARK-7690][ml][WIP] Multiclass Evaluator for ML Pipeline
Project: http://git-wip-us.apache.org/repos/asf/spark/repo
Commit: http://git-wip-us.apache.org/repos/asf/spark/commit/4e5919bf
Tree: http://git-wip-us.apache.org/repos/asf/spark/tree/4e5919bf
Diff: http://git-wip-us.apache.org/repos/asf/spark/diff/4e5919bf
Branch: refs/heads/master
Commit: 4e5919bfb47a58bcbda90ae01c1bed2128ded983
Parents: 83670fc
Author: Ram Sriharsha <rs...@hw11853.local>
Authored: Thu Jul 30 23:02:11 2015 -0700
Committer: Joseph K. Bradley <jo...@databricks.com>
Committed: Thu Jul 30 23:02:11 2015 -0700
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.../MulticlassClassificationEvaluator.scala | 85 ++++++++++++++++++++
...MulticlassClassificationEvaluatorSuite.scala | 28 +++++++
python/pyspark/ml/evaluation.py | 66 +++++++++++++++
3 files changed, 179 insertions(+)
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http://git-wip-us.apache.org/repos/asf/spark/blob/4e5919bf/mllib/src/main/scala/org/apache/spark/ml/evaluation/MulticlassClassificationEvaluator.scala
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diff --git a/mllib/src/main/scala/org/apache/spark/ml/evaluation/MulticlassClassificationEvaluator.scala b/mllib/src/main/scala/org/apache/spark/ml/evaluation/MulticlassClassificationEvaluator.scala
new file mode 100644
index 0000000..44f779c
--- /dev/null
+++ b/mllib/src/main/scala/org/apache/spark/ml/evaluation/MulticlassClassificationEvaluator.scala
@@ -0,0 +1,85 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.ml.evaluation
+
+import org.apache.spark.annotation.Experimental
+import org.apache.spark.ml.param.{ParamMap, ParamValidators, Param}
+import org.apache.spark.ml.param.shared.{HasLabelCol, HasPredictionCol}
+import org.apache.spark.ml.util.{SchemaUtils, Identifiable}
+import org.apache.spark.mllib.evaluation.MulticlassMetrics
+import org.apache.spark.sql.{Row, DataFrame}
+import org.apache.spark.sql.types.DoubleType
+
+/**
+ * :: Experimental ::
+ * Evaluator for multiclass classification, which expects two input columns: score and label.
+ */
+@Experimental
+class MulticlassClassificationEvaluator (override val uid: String)
+ extends Evaluator with HasPredictionCol with HasLabelCol {
+
+ def this() = this(Identifiable.randomUID("mcEval"))
+
+ /**
+ * param for metric name in evaluation (supports `"f1"` (default), `"precision"`, `"recall"`,
+ * `"weightedPrecision"`, `"weightedRecall"`)
+ * @group param
+ */
+ val metricName: Param[String] = {
+ val allowedParams = ParamValidators.inArray(Array("f1", "precision",
+ "recall", "weightedPrecision", "weightedRecall"))
+ new Param(this, "metricName", "metric name in evaluation " +
+ "(f1|precision|recall|weightedPrecision|weightedRecall)", allowedParams)
+ }
+
+ /** @group getParam */
+ def getMetricName: String = $(metricName)
+
+ /** @group setParam */
+ def setMetricName(value: String): this.type = set(metricName, value)
+
+ /** @group setParam */
+ def setPredictionCol(value: String): this.type = set(predictionCol, value)
+
+ /** @group setParam */
+ def setLabelCol(value: String): this.type = set(labelCol, value)
+
+ setDefault(metricName -> "f1")
+
+ override def evaluate(dataset: DataFrame): Double = {
+ val schema = dataset.schema
+ SchemaUtils.checkColumnType(schema, $(predictionCol), DoubleType)
+ SchemaUtils.checkColumnType(schema, $(labelCol), DoubleType)
+
+ val predictionAndLabels = dataset.select($(predictionCol), $(labelCol))
+ .map { case Row(prediction: Double, label: Double) =>
+ (prediction, label)
+ }
+ val metrics = new MulticlassMetrics(predictionAndLabels)
+ val metric = $(metricName) match {
+ case "f1" => metrics.weightedFMeasure
+ case "precision" => metrics.precision
+ case "recall" => metrics.recall
+ case "weightedPrecision" => metrics.weightedPrecision
+ case "weightedRecall" => metrics.weightedRecall
+ }
+ metric
+ }
+
+ override def copy(extra: ParamMap): MulticlassClassificationEvaluator = defaultCopy(extra)
+}
http://git-wip-us.apache.org/repos/asf/spark/blob/4e5919bf/mllib/src/test/scala/org/apache/spark/ml/evaluation/MulticlassClassificationEvaluatorSuite.scala
----------------------------------------------------------------------
diff --git a/mllib/src/test/scala/org/apache/spark/ml/evaluation/MulticlassClassificationEvaluatorSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/evaluation/MulticlassClassificationEvaluatorSuite.scala
new file mode 100644
index 0000000..6d8412b
--- /dev/null
+++ b/mllib/src/test/scala/org/apache/spark/ml/evaluation/MulticlassClassificationEvaluatorSuite.scala
@@ -0,0 +1,28 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.ml.evaluation
+
+import org.apache.spark.SparkFunSuite
+import org.apache.spark.ml.param.ParamsSuite
+
+class MulticlassClassificationEvaluatorSuite extends SparkFunSuite {
+
+ test("params") {
+ ParamsSuite.checkParams(new MulticlassClassificationEvaluator)
+ }
+}
http://git-wip-us.apache.org/repos/asf/spark/blob/4e5919bf/python/pyspark/ml/evaluation.py
----------------------------------------------------------------------
diff --git a/python/pyspark/ml/evaluation.py b/python/pyspark/ml/evaluation.py
index 595593a..06e8093 100644
--- a/python/pyspark/ml/evaluation.py
+++ b/python/pyspark/ml/evaluation.py
@@ -214,6 +214,72 @@ class RegressionEvaluator(JavaEvaluator, HasLabelCol, HasPredictionCol):
kwargs = self.setParams._input_kwargs
return self._set(**kwargs)
+
+@inherit_doc
+class MulticlassClassificationEvaluator(JavaEvaluator, HasLabelCol, HasPredictionCol):
+ """
+ Evaluator for Multiclass Classification, which expects two input
+ columns: prediction and label.
+ >>> scoreAndLabels = [(0.0, 0.0), (0.0, 1.0), (0.0, 0.0),
+ ... (1.0, 0.0), (1.0, 1.0), (1.0, 1.0), (1.0, 1.0), (2.0, 2.0), (2.0, 0.0)]
+ >>> dataset = sqlContext.createDataFrame(scoreAndLabels, ["prediction", "label"])
+ ...
+ >>> evaluator = MulticlassClassificationEvaluator(predictionCol="prediction")
+ >>> evaluator.evaluate(dataset)
+ 0.66...
+ >>> evaluator.evaluate(dataset, {evaluator.metricName: "precision"})
+ 0.66...
+ >>> evaluator.evaluate(dataset, {evaluator.metricName: "recall"})
+ 0.66...
+ """
+ # a placeholder to make it appear in the generated doc
+ metricName = Param(Params._dummy(), "metricName",
+ "metric name in evaluation "
+ "(f1|precision|recall|weightedPrecision|weightedRecall)")
+
+ @keyword_only
+ def __init__(self, predictionCol="prediction", labelCol="label",
+ metricName="f1"):
+ """
+ __init__(self, predictionCol="prediction", labelCol="label", \
+ metricName="f1")
+ """
+ super(MulticlassClassificationEvaluator, self).__init__()
+ self._java_obj = self._new_java_obj(
+ "org.apache.spark.ml.evaluation.MulticlassClassificationEvaluator", self.uid)
+ # param for metric name in evaluation (f1|precision|recall|weightedPrecision|weightedRecall)
+ self.metricName = Param(self, "metricName",
+ "metric name in evaluation"
+ " (f1|precision|recall|weightedPrecision|weightedRecall)")
+ self._setDefault(predictionCol="prediction", labelCol="label",
+ metricName="f1")
+ kwargs = self.__init__._input_kwargs
+ self._set(**kwargs)
+
+ def setMetricName(self, value):
+ """
+ Sets the value of :py:attr:`metricName`.
+ """
+ self._paramMap[self.metricName] = value
+ return self
+
+ def getMetricName(self):
+ """
+ Gets the value of metricName or its default value.
+ """
+ return self.getOrDefault(self.metricName)
+
+ @keyword_only
+ def setParams(self, predictionCol="prediction", labelCol="label",
+ metricName="f1"):
+ """
+ setParams(self, predictionCol="prediction", labelCol="label", \
+ metricName="f1")
+ Sets params for multiclass classification evaluator.
+ """
+ kwargs = self.setParams._input_kwargs
+ return self._set(**kwargs)
+
if __name__ == "__main__":
import doctest
from pyspark.context import SparkContext
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