Github user sethah commented on a diff in the pull request:
https://github.com/apache/spark/pull/15435#discussion_r106492335
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/classification/LogisticRegression.scala
---
@@ -1086,83 +1115,124 @@ private[classification] class MultiClassSummarizer
extends Serializable {
}
/**
- * Abstraction for multinomial Logistic Regression Training results.
- * Currently, the training summary ignores the training weights except
- * for the objective trace.
- */
-sealed trait LogisticRegressionTrainingSummary extends
LogisticRegressionSummary {
-
- /** objective function (scaled loss + regularization) at each iteration.
*/
- def objectiveHistory: Array[Double]
-
- /** Number of training iterations until termination */
- def totalIterations: Int = objectiveHistory.length
-
-}
-
-/**
* Abstraction for Logistic Regression Results for a given model.
*/
sealed trait LogisticRegressionSummary extends Serializable {
/**
* Dataframe output by the model's `transform` method.
*/
+ @Since("2.2.0")
def predictions: DataFrame
/** Field in "predictions" which gives the probability of each class as
a vector. */
+ @Since("2.2.0")
def probabilityCol: String
+ /** Field in "predictions" which gives the prediction of each class as a
vector. */
--- End diff --
"as a Double". Please check this, there are several cases where the
prediction is said to be a vector, but predictions are actually double values
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