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| author | Yanbo Liang <ybliang8@gmail.com> | 2015-08-31 16:06:38 -0700 |
|---|---|---|
| committer | Xiangrui Meng <meng@databricks.com> | 2015-08-31 16:06:38 -0700 |
| commit | fe16fd0b8b717f01151bc659ec3299dab091c97a (patch) | |
| tree | 8a3b9aab821f18a5b0370cf93ae98ec64e5fd194 /mllib | |
| parent | 540bdee93103a73736d282b95db6a8cda8f6a2b1 (diff) | |
| download | spark-fe16fd0b8b717f01151bc659ec3299dab091c97a.tar.gz spark-fe16fd0b8b717f01151bc659ec3299dab091c97a.tar.bz2 spark-fe16fd0b8b717f01151bc659ec3299dab091c97a.zip | |
[SPARK-10349] [ML] OneVsRest use 'when ... otherwise' not UDF to generate new label at binary reduction
Currently OneVsRest use UDF to generate new binary label during training.
Considering that [SPARK-7321](https://issues.apache.org/jira/browse/SPARK-7321) has been merged, we can use ```when ... otherwise``` which will be more efficiency.
Author: Yanbo Liang <ybliang8@gmail.com>
Closes #8519 from yanboliang/spark-10349.
Diffstat (limited to 'mllib')
| -rw-r--r-- | mllib/src/main/scala/org/apache/spark/ml/classification/OneVsRest.scala | 10 |
1 files changed, 2 insertions, 8 deletions
diff --git a/mllib/src/main/scala/org/apache/spark/ml/classification/OneVsRest.scala b/mllib/src/main/scala/org/apache/spark/ml/classification/OneVsRest.scala index c62e132f5d..debc164bf2 100644 --- a/mllib/src/main/scala/org/apache/spark/ml/classification/OneVsRest.scala +++ b/mllib/src/main/scala/org/apache/spark/ml/classification/OneVsRest.scala @@ -91,7 +91,6 @@ final class OneVsRestModel private[ml] ( // add an accumulator column to store predictions of all the models val accColName = "mbc$acc" + UUID.randomUUID().toString val initUDF = udf { () => Map[Int, Double]() } - val mapType = MapType(IntegerType, DoubleType, valueContainsNull = false) val newDataset = dataset.withColumn(accColName, initUDF()) // persist if underlying dataset is not persistent. @@ -195,16 +194,11 @@ final class OneVsRest(override val uid: String) // create k columns, one for each binary classifier. val models = Range(0, numClasses).par.map { index => - val labelUDF = udf { (label: Double) => - if (label.toInt == index) 1.0 else 0.0 - } - // generate new label metadata for the binary problem. - // TODO: use when ... otherwise after SPARK-7321 is merged val newLabelMeta = BinaryAttribute.defaultAttr.withName("label").toMetadata() val labelColName = "mc2b$" + index - val trainingDataset = - multiclassLabeled.withColumn(labelColName, labelUDF(col($(labelCol))), newLabelMeta) + val trainingDataset = multiclassLabeled.withColumn( + labelColName, when(col($(labelCol)) === index.toDouble, 1.0).otherwise(0.0), newLabelMeta) val classifier = getClassifier val paramMap = new ParamMap() paramMap.put(classifier.labelCol -> labelColName) |