Interface BinaryClassificationSummary

All Superinterfaces:
ClassificationSummary, Serializable
All Known Subinterfaces:
BinaryLogisticRegressionSummary, BinaryLogisticRegressionTrainingSummary, BinaryRandomForestClassificationSummary, BinaryRandomForestClassificationTrainingSummary, FMClassificationSummary, FMClassificationTrainingSummary, LinearSVCSummary, LinearSVCTrainingSummary
All Known Implementing Classes:
BinaryLogisticRegressionSummaryImpl, BinaryLogisticRegressionTrainingSummaryImpl, BinaryRandomForestClassificationSummaryImpl, BinaryRandomForestClassificationTrainingSummaryImpl, FMClassificationSummaryImpl, FMClassificationTrainingSummaryImpl, LinearSVCSummaryImpl, LinearSVCTrainingSummaryImpl

public interface BinaryClassificationSummary extends ClassificationSummary
Abstraction for binary classification results for a given model.
  • Method Details

    • areaUnderROC

      double areaUnderROC()
      Computes the area under the receiver operating characteristic (ROC) curve.
      Returns:
      (undocumented)
    • fMeasureByThreshold

      Dataset<Row> fMeasureByThreshold()
      Returns a dataframe with two fields (threshold, F-Measure) curve with beta = 1.0.
      Returns:
      (undocumented)
    • pr

      Dataset<Row> pr()
      Returns the precision-recall curve, which is a Dataframe containing two fields recall, precision with (0.0, 1.0) prepended to it.
      Returns:
      (undocumented)
    • precisionByThreshold

      Dataset<Row> precisionByThreshold()
      Returns a dataframe with two fields (threshold, precision) curve. Every possible probability obtained in transforming the dataset are used as thresholds used in calculating the precision.
      Returns:
      (undocumented)
    • recallByThreshold

      Dataset<Row> recallByThreshold()
      Returns a dataframe with two fields (threshold, recall) curve. Every possible probability obtained in transforming the dataset are used as thresholds used in calculating the recall.
      Returns:
      (undocumented)
    • roc

      Dataset<Row> roc()
      Returns the receiver operating characteristic (ROC) curve, which is a Dataframe having two fields (FPR, TPR) with (0.0, 0.0) prepended and (1.0, 1.0) appended to it. See http://en.wikipedia.org/wiki/Receiver_operating_characteristic
      Returns:
      (undocumented)
    • scoreCol

      String scoreCol()
      Field in "predictions" which gives the probability or rawPrediction of each class as a vector.
      Returns:
      (undocumented)