Unnecessary persist on instances in ml.regression.IsotonicRegression.fit

  override def fit(dataset: Dataset[_]): IsotonicRegressionModel = instrumented { instr =>
    transformSchema(dataset.schema, logging = true)
    // Extract columns from data.  If dataset is persisted, do not persist oldDataset.
    val instances = extractWeightedLabeledPoints(dataset)
    val handlePersistence = dataset.storageLevel == StorageLevel.NONE
    // Unnecessary persist
    if (handlePersistence) instances.persist(StorageLevel.MEMORY_AND_DISK)
    instr.logPipelineStage(this)
    instr.logDataset(dataset)
    instr.logParams(this, labelCol, featuresCol, weightCol, predictionCol, featureIndex, isotonic)
    instr.logNumFeatures(1)
    val isotonicRegression = new MLlibIsotonicRegression().setIsotonic($(isotonic))
    val oldModel = isotonicRegression.run(instances) // Only use once here
    if (handlePersistence) instances.unpersist()