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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