Github user harsha2010 commented on a diff in the pull request:
https://github.com/apache/spark/pull/5830#discussion_r29901844
--- Diff: mllib/src/main/scala/org/apache/spark/ml/reduction/OneVsAll.scala
---
@@ -0,0 +1,165 @@
+/*
+ * 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.reduction
+
+import scala.language.existentials
+import scala.reflect.ClassTag
+
+import org.apache.spark.annotation.{AlphaComponent, Experimental}
+import org.apache.spark.ml.attribute.BinaryAttribute
+import org.apache.spark.ml.classification.{ClassificationModel,
Classifier, ClassifierParams}
+import org.apache.spark.ml.impl.estimator.{PredictionModel, Predictor}
+import org.apache.spark.ml.param.ParamMap
+import org.apache.spark.ml.util.{MetadataUtils, SchemaUtils}
+import org.apache.spark.mllib.linalg.Vector
+import org.apache.spark.rdd.RDD
+import org.apache.spark.sql.{DataFrame, Row}
+import org.apache.spark.sql.functions._
+import org.apache.spark.sql.types._
+import org.apache.spark.storage.StorageLevel
+
+/**
+ * Model produced by [[OneVsAll]].
+ *
+ * @param parent
+ * @param models the binary classification models for reduction.
+ */
+@AlphaComponent
+class OneVsAllModel[
+ FeaturesType,
+ E <: Classifier[FeaturesType, E, M],
+ M <: ClassificationModel[FeaturesType, M]](
+ override val parent: OneVsAll[FeaturesType, E, M],
+ val models: Array[M])
+ extends PredictionModel[FeaturesType, OneVsAllModel[FeaturesType, E, M]]
+ with ClassifierParams {
+
+ override protected def featuresDataType: DataType =
parent.featuresDataType
+
+ override def transformSchema(schema: StructType): StructType = {
+ validateAndTransformSchema(schema, fitting = false, featuresDataType)
+ }
+
+ override def transform(dataset: DataFrame): DataFrame = {
+ // Check schema
+ val parentSchema = dataset.schema
+ transformSchema(parentSchema, logging = true)
+ val sqlCtx = dataset.sqlContext
+
+ // score each model on every data point and pick the model with
highest score
+ // TODO: Use DataFrame expressions to leverage performance here
+ val predictions = models.zipWithIndex.par.map { case (model, index) =>
+ val output = model.transform(dataset)
+ output.select($(rawPredictionCol)).map { case Row(p: Vector) =>
List((index, p(1))) }
+ }.reduce[RDD[List[(Int, Double)]]] { case (x, y) =>
+ x.zip(y).map { case ((a, b)) =>
+ a ++ b
+ }
+ }.map(_.maxBy(_._2))
+
+ // ensure that we pass through columns that are part of the original
dataset.
+ val results = dataset.select(col("*")).rdd.zip(predictions).map { case
(row, (label, _)) =>
+ Row.fromSeq(row.toSeq ++ List(label.toDouble))
+ }
+
+ // the output schema should retain all input fields and add prediction
column.
+ val outputSchema = SchemaUtils.appendColumn(parentSchema,
$(predictionCol), DoubleType)
+ sqlCtx.createDataFrame(results, outputSchema)
+ }
+
+ def predict(features: FeaturesType): Double = {
+ throw new UnsupportedOperationException("Ensemble Classifier does not
support predict," +
+ " use transform instead")
+ }
+}
+
+/**
+ * :: Experimental ::
+ *
+ * Reduction of Multiclass Classification to Binary Classification.
+ * Performs reduction using one against all strategy.
+ * For a multiclass classification with k classes, train k models (one per
class).
+ * Each example is scored against all k models and the model with highest
score
+ * is picked to label the example.
+ *
+ * Classifier parameters like featuresCol, predictionCol and
rawPredictionCol are
+ * set directly on the OneVsRest and are ignored on the underlying
classifier.
+ *
+ */
+@Experimental
+class OneVsAll[
+ FeaturesType,
+ E <: Classifier[FeaturesType, E, M],
+ M <: ClassificationModel[FeaturesType, M]]
+ (val classifier: Classifier[FeaturesType, E, M])
+ (implicit m: ClassTag[M])
+ extends Predictor[FeaturesType, OneVsAll[FeaturesType, E, M],
OneVsAllModel[FeaturesType, E, M]]
+ with ClassifierParams {
--- End diff --
All the base classifier parameters are being set by OneVsAll.
It needs access to rawPredictionCol for example and needs to be able to
set/ read classifier params instead of just params.
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