From 4b70798c96b0a784b85fda461426ec60f609be12 Mon Sep 17 00:00:00 2001
From: Yanbo Liang <ybliang8@gmail.com>
Date: Thu, 13 Aug 2015 09:31:14 -0700
Subject: [PATCH] [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 <ybliang8@gmail.com>
Closes #8164 from yanboliang/mlp-name.
---
.../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)
}
}
--
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