diff options
11 files changed, 14 insertions, 14 deletions
diff --git a/docs/ml-guide.md b/docs/ml-guide.md index c5f50ed799..4eb622d4b9 100644 --- a/docs/ml-guide.md +++ b/docs/ml-guide.md @@ -207,7 +207,7 @@ val model1 = lr.fit(training.toDF) // we can view the parameters it used during fit(). // This prints the parameter (name: value) pairs, where names are unique IDs for this // LogisticRegression instance. -println("Model 1 was fit using parameters: " + model1.fittingParamMap) +println("Model 1 was fit using parameters: " + model1.parent.extractParamMap) // We may alternatively specify parameters using a ParamMap, // which supports several methods for specifying parameters. @@ -222,7 +222,7 @@ val paramMapCombined = paramMap ++ paramMap2 // Now learn a new model using the paramMapCombined parameters. // paramMapCombined overrides all parameters set earlier via lr.set* methods. val model2 = lr.fit(training.toDF, paramMapCombined) -println("Model 2 was fit using parameters: " + model2.fittingParamMap) +println("Model 2 was fit using parameters: " + model2.parent.extractParamMap) // Prepare test data. val test = sc.parallelize(Seq( @@ -289,7 +289,7 @@ LogisticRegressionModel model1 = lr.fit(training); // we can view the parameters it used during fit(). // This prints the parameter (name: value) pairs, where names are unique IDs for this // LogisticRegression instance. -System.out.println("Model 1 was fit using parameters: " + model1.fittingParamMap()); +System.out.println("Model 1 was fit using parameters: " + model1.parent().extractParamMap()); // We may alternatively specify parameters using a ParamMap. ParamMap paramMap = new ParamMap(); @@ -305,7 +305,7 @@ ParamMap paramMapCombined = paramMap.$plus$plus(paramMap2); // Now learn a new model using the paramMapCombined parameters. // paramMapCombined overrides all parameters set earlier via lr.set* methods. LogisticRegressionModel model2 = lr.fit(training, paramMapCombined); -System.out.println("Model 2 was fit using parameters: " + model2.fittingParamMap()); +System.out.println("Model 2 was fit using parameters: " + model2.parent().extractParamMap()); // Prepare test documents. List<LabeledPoint> localTest = Lists.newArrayList( diff --git a/mllib/src/main/scala/org/apache/spark/ml/classification/GBTClassifier.scala b/mllib/src/main/scala/org/apache/spark/ml/classification/GBTClassifier.scala index d8592eb2d9..62f4b51f77 100644 --- a/mllib/src/main/scala/org/apache/spark/ml/classification/GBTClassifier.scala +++ b/mllib/src/main/scala/org/apache/spark/ml/classification/GBTClassifier.scala @@ -208,7 +208,7 @@ private[ml] object GBTClassificationModel { require(oldModel.algo == OldAlgo.Classification, "Cannot convert GradientBoostedTreesModel" + s" with algo=${oldModel.algo} (old API) to GBTClassificationModel (new API).") val newTrees = oldModel.trees.map { tree => - // parent, fittingParamMap for each tree is null since there are no good ways to set these. + // parent for each tree is null since there is no good way to set this. DecisionTreeRegressionModel.fromOld(tree, null, categoricalFeatures) } val uid = if (parent != null) parent.uid else Identifiable.randomUID("gbtc") diff --git a/mllib/src/main/scala/org/apache/spark/ml/classification/RandomForestClassifier.scala b/mllib/src/main/scala/org/apache/spark/ml/classification/RandomForestClassifier.scala index 67600ebd7b..852a67e066 100644 --- a/mllib/src/main/scala/org/apache/spark/ml/classification/RandomForestClassifier.scala +++ b/mllib/src/main/scala/org/apache/spark/ml/classification/RandomForestClassifier.scala @@ -170,7 +170,7 @@ private[ml] object RandomForestClassificationModel { require(oldModel.algo == OldAlgo.Classification, "Cannot convert RandomForestModel" + s" with algo=${oldModel.algo} (old API) to RandomForestClassificationModel (new API).") val newTrees = oldModel.trees.map { tree => - // parent, fittingParamMap for each tree is null since there are no good ways to set these. + // parent for each tree is null since there is no good way to set this. DecisionTreeClassificationModel.fromOld(tree, null, categoricalFeatures) } val uid = if (parent != null) parent.uid else Identifiable.randomUID("rfc") diff --git a/mllib/src/main/scala/org/apache/spark/ml/regression/GBTRegressor.scala b/mllib/src/main/scala/org/apache/spark/ml/regression/GBTRegressor.scala index 69f4f5414c..b7e374bb6c 100644 --- a/mllib/src/main/scala/org/apache/spark/ml/regression/GBTRegressor.scala +++ b/mllib/src/main/scala/org/apache/spark/ml/regression/GBTRegressor.scala @@ -198,7 +198,7 @@ private[ml] object GBTRegressionModel { require(oldModel.algo == OldAlgo.Regression, "Cannot convert GradientBoostedTreesModel" + s" with algo=${oldModel.algo} (old API) to GBTRegressionModel (new API).") val newTrees = oldModel.trees.map { tree => - // parent, fittingParamMap for each tree is null since there are no good ways to set these. + // parent for each tree is null since there is no good way to set this. DecisionTreeRegressionModel.fromOld(tree, null, categoricalFeatures) } val uid = if (parent != null) parent.uid else Identifiable.randomUID("gbtr") diff --git a/mllib/src/main/scala/org/apache/spark/ml/regression/RandomForestRegressor.scala b/mllib/src/main/scala/org/apache/spark/ml/regression/RandomForestRegressor.scala index ae767a1732..49a1f7ce8c 100644 --- a/mllib/src/main/scala/org/apache/spark/ml/regression/RandomForestRegressor.scala +++ b/mllib/src/main/scala/org/apache/spark/ml/regression/RandomForestRegressor.scala @@ -152,7 +152,7 @@ private[ml] object RandomForestRegressionModel { require(oldModel.algo == OldAlgo.Regression, "Cannot convert RandomForestModel" + s" with algo=${oldModel.algo} (old API) to RandomForestRegressionModel (new API).") val newTrees = oldModel.trees.map { tree => - // parent, fittingParamMap for each tree is null since there are no good ways to set these. + // parent for each tree is null since there is no good way to set this. DecisionTreeRegressionModel.fromOld(tree, null, categoricalFeatures) } new RandomForestRegressionModel(parent.uid, newTrees) diff --git a/mllib/src/test/scala/org/apache/spark/ml/classification/DecisionTreeClassifierSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/classification/DecisionTreeClassifierSuite.scala index 40554f6ef9..ae40b0b8ff 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/classification/DecisionTreeClassifierSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/classification/DecisionTreeClassifierSuite.scala @@ -265,7 +265,7 @@ private[ml] object DecisionTreeClassifierSuite extends SparkFunSuite { val oldTree = OldDecisionTree.train(data, oldStrategy) val newData: DataFrame = TreeTests.setMetadata(data, categoricalFeatures, numClasses) val newTree = dt.fit(newData) - // Use parent, fittingParamMap from newTree since these are not checked anyways. + // Use parent from newTree since this is not checked anyways. val oldTreeAsNew = DecisionTreeClassificationModel.fromOld( oldTree, newTree.parent.asInstanceOf[DecisionTreeClassifier], categoricalFeatures) TreeTests.checkEqual(oldTreeAsNew, newTree) diff --git a/mllib/src/test/scala/org/apache/spark/ml/classification/GBTClassifierSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/classification/GBTClassifierSuite.scala index 0932705162..1302da3c37 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/classification/GBTClassifierSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/classification/GBTClassifierSuite.scala @@ -127,7 +127,7 @@ private object GBTClassifierSuite { val oldModel = oldGBT.run(data) val newData: DataFrame = TreeTests.setMetadata(data, categoricalFeatures, numClasses = 2) val newModel = gbt.fit(newData) - // Use parent, fittingParamMap from newTree since these are not checked anyways. + // Use parent from newTree since this is not checked anyways. val oldModelAsNew = GBTClassificationModel.fromOld( oldModel, newModel.parent.asInstanceOf[GBTClassifier], categoricalFeatures) TreeTests.checkEqual(oldModelAsNew, newModel) diff --git a/mllib/src/test/scala/org/apache/spark/ml/classification/RandomForestClassifierSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/classification/RandomForestClassifierSuite.scala index f699d0c374..eee9355a67 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/classification/RandomForestClassifierSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/classification/RandomForestClassifierSuite.scala @@ -157,7 +157,7 @@ private object RandomForestClassifierSuite { data, oldStrategy, rf.getNumTrees, rf.getFeatureSubsetStrategy, rf.getSeed.toInt) val newData: DataFrame = TreeTests.setMetadata(data, categoricalFeatures, numClasses) val newModel = rf.fit(newData) - // Use parent, fittingParamMap from newTree since these are not checked anyways. + // Use parent from newTree since this is not checked anyways. val oldModelAsNew = RandomForestClassificationModel.fromOld( oldModel, newModel.parent.asInstanceOf[RandomForestClassifier], categoricalFeatures) TreeTests.checkEqual(oldModelAsNew, newModel) diff --git a/mllib/src/test/scala/org/apache/spark/ml/regression/DecisionTreeRegressorSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/regression/DecisionTreeRegressorSuite.scala index 1182b89a8e..33aa9d0d62 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/regression/DecisionTreeRegressorSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/regression/DecisionTreeRegressorSuite.scala @@ -82,7 +82,7 @@ private[ml] object DecisionTreeRegressorSuite extends SparkFunSuite { val oldTree = OldDecisionTree.train(data, oldStrategy) val newData: DataFrame = TreeTests.setMetadata(data, categoricalFeatures, numClasses = 0) val newTree = dt.fit(newData) - // Use parent, fittingParamMap from newTree since these are not checked anyways. + // Use parent from newTree since this is not checked anyways. val oldTreeAsNew = DecisionTreeRegressionModel.fromOld( oldTree, newTree.parent.asInstanceOf[DecisionTreeRegressor], categoricalFeatures) TreeTests.checkEqual(oldTreeAsNew, newTree) diff --git a/mllib/src/test/scala/org/apache/spark/ml/regression/GBTRegressorSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/regression/GBTRegressorSuite.scala index f8a1469fee..98fb3d3f5f 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/regression/GBTRegressorSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/regression/GBTRegressorSuite.scala @@ -128,7 +128,7 @@ private object GBTRegressorSuite { val oldModel = oldGBT.run(data) val newData: DataFrame = TreeTests.setMetadata(data, categoricalFeatures, numClasses = 0) val newModel = gbt.fit(newData) - // Use parent, fittingParamMap from newTree since these are not checked anyways. + // Use parent from newTree since this is not checked anyways. val oldModelAsNew = GBTRegressionModel.fromOld( oldModel, newModel.parent.asInstanceOf[GBTRegressor], categoricalFeatures) TreeTests.checkEqual(oldModelAsNew, newModel) diff --git a/mllib/src/test/scala/org/apache/spark/ml/regression/RandomForestRegressorSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/regression/RandomForestRegressorSuite.scala index 7891156094..b24ecaa57c 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/regression/RandomForestRegressorSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/regression/RandomForestRegressorSuite.scala @@ -113,7 +113,7 @@ private object RandomForestRegressorSuite extends SparkFunSuite { data, oldStrategy, rf.getNumTrees, rf.getFeatureSubsetStrategy, rf.getSeed.toInt) val newData: DataFrame = TreeTests.setMetadata(data, categoricalFeatures, numClasses = 0) val newModel = rf.fit(newData) - // Use parent, fittingParamMap from newTree since these are not checked anyways. + // Use parent from newTree since this is not checked anyways. val oldModelAsNew = RandomForestRegressionModel.fromOld( oldModel, newModel.parent.asInstanceOf[RandomForestRegressor], categoricalFeatures) TreeTests.checkEqual(oldModelAsNew, newModel) |