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Posted to commits@spark.apache.org by me...@apache.org on 2015/10/21 01:13:40 UTC
spark git commit: [SPARK-10261][DOCUMENTATION,
ML] Fixed @Since annotation to ml.evaluation
Repository: spark
Updated Branches:
refs/heads/master 82e9d9c81 -> 9f49895fe
[SPARK-10261][DOCUMENTATION, ML] Fixed @Since annotation to ml.evaluation
Author: Tijo Thomas <ti...@gmail.com>
Author: tijo <ti...@ezzoft.com>
Closes #8554 from tijoparacka/SPARK-10261-2.
Project: http://git-wip-us.apache.org/repos/asf/spark/repo
Commit: http://git-wip-us.apache.org/repos/asf/spark/commit/9f49895f
Tree: http://git-wip-us.apache.org/repos/asf/spark/tree/9f49895f
Diff: http://git-wip-us.apache.org/repos/asf/spark/diff/9f49895f
Branch: refs/heads/master
Commit: 9f49895fefc294ef40b2e974f1f8b311087c54df
Parents: 82e9d9c
Author: Tijo Thomas <ti...@gmail.com>
Authored: Tue Oct 20 16:13:34 2015 -0700
Committer: Xiangrui Meng <me...@databricks.com>
Committed: Tue Oct 20 16:13:34 2015 -0700
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.../evaluation/BinaryClassificationEvaluator.scala | 15 +++++++++++++--
.../org/apache/spark/ml/evaluation/Evaluator.scala | 7 ++++++-
.../MulticlassClassificationEvaluator.scala | 14 ++++++++++++--
.../spark/ml/evaluation/RegressionEvaluator.scala | 14 ++++++++++++--
4 files changed, 43 insertions(+), 7 deletions(-)
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http://git-wip-us.apache.org/repos/asf/spark/blob/9f49895f/mllib/src/main/scala/org/apache/spark/ml/evaluation/BinaryClassificationEvaluator.scala
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diff --git a/mllib/src/main/scala/org/apache/spark/ml/evaluation/BinaryClassificationEvaluator.scala b/mllib/src/main/scala/org/apache/spark/ml/evaluation/BinaryClassificationEvaluator.scala
index 08df291..1fe3aba 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/evaluation/BinaryClassificationEvaluator.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/evaluation/BinaryClassificationEvaluator.scala
@@ -17,7 +17,7 @@
package org.apache.spark.ml.evaluation
-import org.apache.spark.annotation.Experimental
+import org.apache.spark.annotation.{Experimental, Since}
import org.apache.spark.ml.param._
import org.apache.spark.ml.param.shared._
import org.apache.spark.ml.util.{Identifiable, SchemaUtils}
@@ -30,10 +30,12 @@ import org.apache.spark.sql.types.DoubleType
* :: Experimental ::
* Evaluator for binary classification, which expects two input columns: rawPrediction and label.
*/
+@Since("1.2.0")
@Experimental
-class BinaryClassificationEvaluator(override val uid: String)
+class BinaryClassificationEvaluator @Since("1.4.0") (@Since("1.4.0") override val uid: String)
extends Evaluator with HasRawPredictionCol with HasLabelCol {
+ @Since("1.2.0")
def this() = this(Identifiable.randomUID("binEval"))
/**
@@ -41,6 +43,7 @@ class BinaryClassificationEvaluator(override val uid: String)
* Default: areaUnderROC
* @group param
*/
+ @Since("1.2.0")
val metricName: Param[String] = {
val allowedParams = ParamValidators.inArray(Array("areaUnderROC", "areaUnderPR"))
new Param(
@@ -48,12 +51,15 @@ class BinaryClassificationEvaluator(override val uid: String)
}
/** @group getParam */
+ @Since("1.2.0")
def getMetricName: String = $(metricName)
/** @group setParam */
+ @Since("1.2.0")
def setMetricName(value: String): this.type = set(metricName, value)
/** @group setParam */
+ @Since("1.5.0")
def setRawPredictionCol(value: String): this.type = set(rawPredictionCol, value)
/**
@@ -61,13 +67,16 @@ class BinaryClassificationEvaluator(override val uid: String)
* @deprecated use [[setRawPredictionCol()]] instead
*/
@deprecated("use setRawPredictionCol instead", "1.5.0")
+ @Since("1.2.0")
def setScoreCol(value: String): this.type = set(rawPredictionCol, value)
/** @group setParam */
+ @Since("1.2.0")
def setLabelCol(value: String): this.type = set(labelCol, value)
setDefault(metricName -> "areaUnderROC")
+ @Since("1.2.0")
override def evaluate(dataset: DataFrame): Double = {
val schema = dataset.schema
SchemaUtils.checkColumnType(schema, $(rawPredictionCol), new VectorUDT)
@@ -87,10 +96,12 @@ class BinaryClassificationEvaluator(override val uid: String)
metric
}
+ @Since("1.5.0")
override def isLargerBetter: Boolean = $(metricName) match {
case "areaUnderROC" => true
case "areaUnderPR" => true
}
+ @Since("1.4.1")
override def copy(extra: ParamMap): BinaryClassificationEvaluator = defaultCopy(extra)
}
http://git-wip-us.apache.org/repos/asf/spark/blob/9f49895f/mllib/src/main/scala/org/apache/spark/ml/evaluation/Evaluator.scala
----------------------------------------------------------------------
diff --git a/mllib/src/main/scala/org/apache/spark/ml/evaluation/Evaluator.scala b/mllib/src/main/scala/org/apache/spark/ml/evaluation/Evaluator.scala
index 13bd330..0f22cca 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/evaluation/Evaluator.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/evaluation/Evaluator.scala
@@ -17,7 +17,7 @@
package org.apache.spark.ml.evaluation
-import org.apache.spark.annotation.DeveloperApi
+import org.apache.spark.annotation.{DeveloperApi, Since}
import org.apache.spark.ml.param.{ParamMap, Params}
import org.apache.spark.sql.DataFrame
@@ -25,6 +25,7 @@ import org.apache.spark.sql.DataFrame
* :: DeveloperApi ::
* Abstract class for evaluators that compute metrics from predictions.
*/
+@Since("1.5.0")
@DeveloperApi
abstract class Evaluator extends Params {
@@ -35,6 +36,7 @@ abstract class Evaluator extends Params {
* @param paramMap parameter map that specifies the input columns and output metrics
* @return metric
*/
+ @Since("1.5.0")
def evaluate(dataset: DataFrame, paramMap: ParamMap): Double = {
this.copy(paramMap).evaluate(dataset)
}
@@ -44,6 +46,7 @@ abstract class Evaluator extends Params {
* @param dataset a dataset that contains labels/observations and predictions.
* @return metric
*/
+ @Since("1.5.0")
def evaluate(dataset: DataFrame): Double
/**
@@ -51,7 +54,9 @@ abstract class Evaluator extends Params {
* or minimized (false).
* A given evaluator may support multiple metrics which may be maximized or minimized.
*/
+ @Since("1.5.0")
def isLargerBetter: Boolean = true
+ @Since("1.5.0")
override def copy(extra: ParamMap): Evaluator
}
http://git-wip-us.apache.org/repos/asf/spark/blob/9f49895f/mllib/src/main/scala/org/apache/spark/ml/evaluation/MulticlassClassificationEvaluator.scala
----------------------------------------------------------------------
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
index f73d234..df5f04c 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/evaluation/MulticlassClassificationEvaluator.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/evaluation/MulticlassClassificationEvaluator.scala
@@ -17,7 +17,7 @@
package org.apache.spark.ml.evaluation
-import org.apache.spark.annotation.Experimental
+import org.apache.spark.annotation.{Experimental, Since}
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}
@@ -29,10 +29,12 @@ import org.apache.spark.sql.types.DoubleType
* :: Experimental ::
* Evaluator for multiclass classification, which expects two input columns: score and label.
*/
+@Since("1.5.0")
@Experimental
-class MulticlassClassificationEvaluator (override val uid: String)
+class MulticlassClassificationEvaluator @Since("1.5.0") (@Since("1.5.0") override val uid: String)
extends Evaluator with HasPredictionCol with HasLabelCol {
+ @Since("1.5.0")
def this() = this(Identifiable.randomUID("mcEval"))
/**
@@ -40,6 +42,7 @@ class MulticlassClassificationEvaluator (override val uid: String)
* `"weightedPrecision"`, `"weightedRecall"`)
* @group param
*/
+ @Since("1.5.0")
val metricName: Param[String] = {
val allowedParams = ParamValidators.inArray(Array("f1", "precision",
"recall", "weightedPrecision", "weightedRecall"))
@@ -48,19 +51,24 @@ class MulticlassClassificationEvaluator (override val uid: String)
}
/** @group getParam */
+ @Since("1.5.0")
def getMetricName: String = $(metricName)
/** @group setParam */
+ @Since("1.5.0")
def setMetricName(value: String): this.type = set(metricName, value)
/** @group setParam */
+ @Since("1.5.0")
def setPredictionCol(value: String): this.type = set(predictionCol, value)
/** @group setParam */
+ @Since("1.5.0")
def setLabelCol(value: String): this.type = set(labelCol, value)
setDefault(metricName -> "f1")
+ @Since("1.5.0")
override def evaluate(dataset: DataFrame): Double = {
val schema = dataset.schema
SchemaUtils.checkColumnType(schema, $(predictionCol), DoubleType)
@@ -81,6 +89,7 @@ class MulticlassClassificationEvaluator (override val uid: String)
metric
}
+ @Since("1.5.0")
override def isLargerBetter: Boolean = $(metricName) match {
case "f1" => true
case "precision" => true
@@ -89,5 +98,6 @@ class MulticlassClassificationEvaluator (override val uid: String)
case "weightedRecall" => true
}
+ @Since("1.5.0")
override def copy(extra: ParamMap): MulticlassClassificationEvaluator = defaultCopy(extra)
}
http://git-wip-us.apache.org/repos/asf/spark/blob/9f49895f/mllib/src/main/scala/org/apache/spark/ml/evaluation/RegressionEvaluator.scala
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diff --git a/mllib/src/main/scala/org/apache/spark/ml/evaluation/RegressionEvaluator.scala b/mllib/src/main/scala/org/apache/spark/ml/evaluation/RegressionEvaluator.scala
index d21c88a..3fd34d8 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/evaluation/RegressionEvaluator.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/evaluation/RegressionEvaluator.scala
@@ -17,7 +17,7 @@
package org.apache.spark.ml.evaluation
-import org.apache.spark.annotation.Experimental
+import org.apache.spark.annotation.{Experimental, Since}
import org.apache.spark.ml.param.{Param, ParamMap, ParamValidators}
import org.apache.spark.ml.param.shared.{HasLabelCol, HasPredictionCol}
import org.apache.spark.ml.util.{Identifiable, SchemaUtils}
@@ -29,10 +29,12 @@ import org.apache.spark.sql.types.DoubleType
* :: Experimental ::
* Evaluator for regression, which expects two input columns: prediction and label.
*/
+@Since("1.4.0")
@Experimental
-final class RegressionEvaluator(override val uid: String)
+final class RegressionEvaluator @Since("1.4.0") (@Since("1.4.0") override val uid: String)
extends Evaluator with HasPredictionCol with HasLabelCol {
+ @Since("1.4.0")
def this() = this(Identifiable.randomUID("regEval"))
/**
@@ -43,25 +45,31 @@ final class RegressionEvaluator(override val uid: String)
* we take and output the negative of this metric.
* @group param
*/
+ @Since("1.4.0")
val metricName: Param[String] = {
val allowedParams = ParamValidators.inArray(Array("mse", "rmse", "r2", "mae"))
new Param(this, "metricName", "metric name in evaluation (mse|rmse|r2|mae)", allowedParams)
}
/** @group getParam */
+ @Since("1.4.0")
def getMetricName: String = $(metricName)
/** @group setParam */
+ @Since("1.4.0")
def setMetricName(value: String): this.type = set(metricName, value)
/** @group setParam */
+ @Since("1.4.0")
def setPredictionCol(value: String): this.type = set(predictionCol, value)
/** @group setParam */
+ @Since("1.4.0")
def setLabelCol(value: String): this.type = set(labelCol, value)
setDefault(metricName -> "rmse")
+ @Since("1.4.0")
override def evaluate(dataset: DataFrame): Double = {
val schema = dataset.schema
SchemaUtils.checkColumnType(schema, $(predictionCol), DoubleType)
@@ -81,6 +89,7 @@ final class RegressionEvaluator(override val uid: String)
metric
}
+ @Since("1.4.0")
override def isLargerBetter: Boolean = $(metricName) match {
case "rmse" => false
case "mse" => false
@@ -88,5 +97,6 @@ final class RegressionEvaluator(override val uid: String)
case "mae" => false
}
+ @Since("1.5.0")
override def copy(extra: ParamMap): RegressionEvaluator = defaultCopy(extra)
}
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