Github user sethah commented on a diff in the pull request: https://github.com/apache/spark/pull/10607#discussion_r48907580 --- Diff: mllib/src/main/scala/org/apache/spark/ml/tree/impl/GradientBoostedTrees.scala --- @@ -0,0 +1,272 @@ +/* + * 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.tree.impl + +import org.apache.spark.Logging +import org.apache.spark.mllib.impl.PeriodicRDDCheckpointer +import org.apache.spark.mllib.regression.LabeledPoint +import org.apache.spark.ml.regression.{DecisionTreeRegressionModel, DecisionTreeRegressor} +import org.apache.spark.mllib.tree.configuration.Algo._ +import org.apache.spark.mllib.tree.configuration.BoostingStrategy +import org.apache.spark.mllib.tree.impl.TimeTracker +import org.apache.spark.mllib.tree.impurity.Variance +import org.apache.spark.mllib.tree.loss.Loss +import org.apache.spark.rdd.RDD +import org.apache.spark.storage.StorageLevel + +private[ml] object GradientBoostedTrees extends Logging { + + /** + * Method to train a gradient boosting model + * @param input Training dataset: RDD of [[org.apache.spark.mllib.regression.LabeledPoint]]. + * @return a gradient boosted trees model that can be used for prediction + */ + def run(input: RDD[LabeledPoint], --- End diff -- `run` and `runWithValidation` were part of the public API in MLlib, but would not be in this implementation. I don't see this as a problem since these weren't available for spark.ml before.
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