Github user mengxr commented on a diff in the pull request:
https://github.com/apache/spark/pull/7621#discussion_r35689295
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/classification/MultilayerPerceptronClassifier.scala
---
@@ -0,0 +1,130 @@
+/*
+ * 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.classification
+
+import breeze.linalg.{argmax => Bargmax}
+
+import org.apache.spark.annotation.Experimental
+import org.apache.spark.ml.{PredictionModel, Predictor}
+import org.apache.spark.ml.param.ParamMap
+import org.apache.spark.ml.util.Identifiable
+import org.apache.spark.ml.regression.MultilayerPerceptronParams
+import org.apache.spark.mllib.ann.{FeedForwardTrainer, FeedForwardTopology}
+import org.apache.spark.mllib.linalg.{Vectors, Vector}
+import org.apache.spark.mllib.regression.LabeledPoint
+import org.apache.spark.sql.DataFrame
+
+/**
+ * :: Experimental ::
+ * Label to vector converter.
+ */
+@Experimental
+private object LabelConverter {
+
+ /**
+ * Encodes a label as a vector.
+ * Returns a vector of given length with zeroes at all positions
+ * and value 1.0 at the position that corresponds to the label.
+ *
+ * @param labeledPoint labeled point
+ * @param labelCount total number of labels
+ * @return vector encoding of a label
+ */
+ def apply(labeledPoint: LabeledPoint, labelCount: Int): (Vector, Vector)
= {
+ val output = Array.fill(labelCount){0.0}
+ output(labeledPoint.label.toInt) = 1.0
+ (labeledPoint.features, Vectors.dense(output))
+ }
+
+ /**
+ * Converts a vector to a label.
+ * Returns the position of the maximal element of a vector.
+ *
+ * @param output label encoded with a vector
+ * @return label
+ */
+ def apply(output: Vector): Double = {
+ Bargmax(output.toBreeze.toDenseVector).toDouble
--- End diff --
`output.argmax` should work. We recently merged `Vector.argmax`.
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