code: static public ModelMetricsRegression make(Vec predicted, Vec actual, DistributionFamily family) {
      if (predicted == null || actual == null)
        throw new IllegalArgumentException("Missing actual or predicted targets for regression metrics!");
      if (!predicted.isNumeric())
        throw new IllegalArgumentException("Predicted values must be numeric for regression metrics.");
      if (!actual.isNumeric())
        throw new IllegalArgumentException("Actual values must be numeric for regression metrics.");
      if (family == DistributionFamily.quantile || family == DistributionFamily.tweedie || family == DistributionFamily.huber)
        throw new IllegalArgumentException("Unsupported distribution family, requires additional parameters which cannot be specified right now.");
      Frame predsActual = new Frame(predicted);
      predsActual.add("actual", actual);
      MetricBuilderRegression mb = new RegressionMetrics(family).doAll(predsActual)._mb;
      ModelMetricsRegression mm = (ModelMetricsRegression)mb.makeModelMetrics(null, predsActual, null, null);
      mm._description = "Computed on user-given predictions and targets, distribution: " + (family ==null? DistributionFamily.gaussian.toString(): family.toString()) + ".";
      return mm;
    }
docs: Build a Regression ModelMetrics object from predicted and actual targets
  @param predicted A Vec containing predicted values
  @param actual A Vec containing the actual target values
  @return ModelMetrics object