Github user MLnick commented on a diff in the pull request: https://github.com/apache/spark/pull/16158#discussion_r131133463 --- Diff: mllib/src/main/scala/org/apache/spark/ml/tuning/TuningSummary.scala --- @@ -0,0 +1,58 @@ +/* + * 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.tuning + +import org.apache.spark.annotation.{Experimental, Since} +import org.apache.spark.ml.param.ParamMap +import org.apache.spark.sql.{DataFrame, Row, SparkSession} +import org.apache.spark.sql.types.{StringType, StructField, StructType} + +/** + * :: Experimental :: + * Summary for the grid search tuning. + * + * @param params ParamMaps for the Estimator + * @param metrics corresponding evaluation metrics for the params + * @param bestIndex index in params for the ParamMap of the best model. + */ +@Since("2.3.0") +@Experimental +private[tuning] class TuningSummary private[tuning]( + private[tuning] val params: Array[ParamMap], + private[tuning] val metrics: Array[Double], + private[tuning] val bestIndex: Int) { + + /** + * Summary of grid search tuning in the format of DataFrame. Each row contains one candidate + * paramMap and its corresponding metric. + */ + def trainingMetrics: DataFrame = { + require(params.nonEmpty, "estimator param maps should not be empty") + require(params.length == metrics.length, "estimator param maps number should match metrics") + val spark = SparkSession.builder().getOrCreate() + val sqlContext = spark.sqlContext + val sc = spark.sparkContext + val fields = params(0).toSeq.sortBy(_.param.name).map(_.param.name) ++ Seq("metrics") --- End diff -- "metrics" is a bit generic. Perhaps it's better (and more user-friendly) to make this be something like `metric_name metric` so that it's obvious what metric was being optimized for? such as `ROC metric` or `AUC metric` or `MSE metric`? etc
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