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There is a newer version: 3.8.2.9
package water.api;

import hex.AUC2;
import hex.ModelMetricsBinomial;
import water.util.TwoDimTable;

import java.util.Arrays;

public class ModelMetricsBinomialV3> extends ModelMetricsBase {
//  @API(help="The standard deviation of the training response.", direction=API.Direction.OUTPUT)
//  public double sigma; // Belongs in a mythical ModelMetricsSupervisedV3

  @API(help="The R^2 for this scoring run.", direction=API.Direction.OUTPUT)
  public double r2;

  @API(help="The logarithmic loss for this scoring run.", direction=API.Direction.OUTPUT)
  public double logloss;

  @API(help="The AUC for this scoring run.", direction=API.Direction.OUTPUT)
  public double AUC;

  @API(help="The Gini score for this scoring run.", direction=API.Direction.OUTPUT)
  public double Gini;

  @API(help="The class labels of the response.", direction=API.Direction.OUTPUT)
  public String[] domain;

//  @API(help = "The ConfusionMatrix at the threshold for maximum F1.", direction = API.Direction.OUTPUT)
//  public ConfusionMatrixBase cm;

  @API(help = "The Metrics for various thresholds.", direction = API.Direction.OUTPUT, level = API.Level.expert)
  public TwoDimTableBase thresholds_and_metric_scores;

  @API(help = "The Metrics for various criteria.", direction = API.Direction.OUTPUT, level = API.Level.secondary)
  public TwoDimTableBase max_criteria_and_metric_scores;

  @API(help = "Gains and Lift table.", direction = API.Direction.OUTPUT, level = API.Level.secondary)
  public TwoDimTableBase gains_lift_table;

  @Override
  public S fillFromImpl(ModelMetricsBinomial modelMetrics) {
    super.fillFromImpl(modelMetrics);
//    sigma = modelMetrics._sigma;
    r2 = modelMetrics.r2();
    logloss = modelMetrics._logloss;

    AUC2 auc = modelMetrics._auc;
    if (null != auc) {
      AUC  = auc._auc;
      Gini = auc._gini;

      // Fill TwoDimTable
      String[] thresholds = new String[auc._nBins];
      for( int i=0; i i) colHeadersMax[i] = "max " + crits[i].toString();
        colHeaders[i+1] = crits[i].toString();
        types     [i+1] = crits[i]._isInt ? "long" : "double";
        formats   [i+1] = crits[i]._isInt ? "%d"   : "%f"    ;
      }
      colHeaders[i+1]  = "idx"; types[i+1] = "int"; formats[i+1] = "%d";
      TwoDimTable thresholdsByMetrics = new TwoDimTable("Metrics for Thresholds", "Binomial metrics as a function of classification thresholds", new String[auc._nBins], colHeaders, types, formats, null );
      for( i=0; i