From 4b70798c96b0a784b85fda461426ec60f609be12 Mon Sep 17 00:00:00 2001 From: Yanbo Liang Date: Thu, 13 Aug 2015 09:31:14 -0700 Subject: [MINOR] [ML] change MultilayerPerceptronClassifierModel to MultilayerPerceptronClassificationModel To follow the naming rule of ML, change `MultilayerPerceptronClassifierModel` to `MultilayerPerceptronClassificationModel` like `DecisionTreeClassificationModel`, `GBTClassificationModel` and so on. Author: Yanbo Liang Closes #8164 from yanboliang/mlp-name. --- .../classification/MultilayerPerceptronClassifier.scala | 16 ++++++++-------- 1 file changed, 8 insertions(+), 8 deletions(-) diff --git a/mllib/src/main/scala/org/apache/spark/ml/classification/MultilayerPerceptronClassifier.scala b/mllib/src/main/scala/org/apache/spark/ml/classification/MultilayerPerceptronClassifier.scala index 8cd2103d7d..c154561886 100644 --- a/mllib/src/main/scala/org/apache/spark/ml/classification/MultilayerPerceptronClassifier.scala +++ b/mllib/src/main/scala/org/apache/spark/ml/classification/MultilayerPerceptronClassifier.scala @@ -131,7 +131,7 @@ private object LabelConverter { */ @Experimental class MultilayerPerceptronClassifier(override val uid: String) - extends Predictor[Vector, MultilayerPerceptronClassifier, MultilayerPerceptronClassifierModel] + extends Predictor[Vector, MultilayerPerceptronClassifier, MultilayerPerceptronClassificationModel] with MultilayerPerceptronParams { def this() = this(Identifiable.randomUID("mlpc")) @@ -146,7 +146,7 @@ class MultilayerPerceptronClassifier(override val uid: String) * @param dataset Training dataset * @return Fitted model */ - override protected def train(dataset: DataFrame): MultilayerPerceptronClassifierModel = { + override protected def train(dataset: DataFrame): MultilayerPerceptronClassificationModel = { val myLayers = $(layers) val labels = myLayers.last val lpData = extractLabeledPoints(dataset) @@ -156,13 +156,13 @@ class MultilayerPerceptronClassifier(override val uid: String) FeedForwardTrainer.LBFGSOptimizer.setConvergenceTol($(tol)).setNumIterations($(maxIter)) FeedForwardTrainer.setStackSize($(blockSize)) val mlpModel = FeedForwardTrainer.train(data) - new MultilayerPerceptronClassifierModel(uid, myLayers, mlpModel.weights()) + new MultilayerPerceptronClassificationModel(uid, myLayers, mlpModel.weights()) } } /** * :: Experimental :: - * Classifier model based on the Multilayer Perceptron. + * Classification model based on the Multilayer Perceptron. * Each layer has sigmoid activation function, output layer has softmax. * @param uid uid * @param layers array of layer sizes including input and output layers @@ -170,11 +170,11 @@ class MultilayerPerceptronClassifier(override val uid: String) * @return prediction model */ @Experimental -class MultilayerPerceptronClassifierModel private[ml] ( +class MultilayerPerceptronClassificationModel private[ml] ( override val uid: String, layers: Array[Int], weights: Vector) - extends PredictionModel[Vector, MultilayerPerceptronClassifierModel] + extends PredictionModel[Vector, MultilayerPerceptronClassificationModel] with Serializable { private val mlpModel = FeedForwardTopology.multiLayerPerceptron(layers, true).getInstance(weights) @@ -187,7 +187,7 @@ class MultilayerPerceptronClassifierModel private[ml] ( LabelConverter.decodeLabel(mlpModel.predict(features)) } - override def copy(extra: ParamMap): MultilayerPerceptronClassifierModel = { - copyValues(new MultilayerPerceptronClassifierModel(uid, layers, weights), extra) + override def copy(extra: ParamMap): MultilayerPerceptronClassificationModel = { + copyValues(new MultilayerPerceptronClassificationModel(uid, layers, weights), extra) } } -- cgit v1.2.3