/** * Get the mean vector. * @return mean vector */ public double[] getResult() { double[] result = new double[means.length]; for (int i = 0; i < result.length; ++i) { result[i] = means[i].getResult(); } return result; }
public AggregateResult(Context accum) { this.mrr = accum.allMean.getResult(); } }
public AggregateResult(Context accum) { this.map = accum.allMean.getResult(); } }
@Override public double mean() { return mean.getResult(); }
@Nonnull @Override public MetricResult getAggregateMeasurements(Mean context) { return MetricResult.singleton(columnName, context.getResult()); }
@Nonnull @Override public MetricResult getAggregateMeasurements(Mean context) { logger.warn("Predict nDCG is deprecated, use nDCG in a rank context"); return MetricResult.singleton(columnName, context.getResult()); }
@Nonnull @Override public MetricResult getAggregateMeasurements(Mean context) { return new LengthResult(context.getResult()); }
@Nonnull @Override public MetricResult getAggregateMeasurements(Context context) { return new PopResult(context.mean.getResult()); }
/** * Get the mean vector. * @return mean vector */ public double[] getResult() { double[] result = new double[means.length]; for (int i = 0; i < result.length; ++i) { result[i] = means[i].getResult(); } return result; }
public double getDindexUpper(){ if(dIndex){ return upper.getResult(); }else{ return Double.NaN; } }
/** * Mean square error of the estimate. * * @return mean square error. */ public double meanSquareError(){ return mean.getResult(); }
public double getDindexLower(){ if(dIndex){ return lower.getResult(); }else{ return Double.NaN; } }
/** * Get the mean vector. * @return mean vector */ public double[] getResult() { double[] result = new double[means.length]; for (int i = 0; i < result.length; ++i) { result[i] = means[i].getResult(); } return result; }
/** * Returns the mean of the values that have been added. * * <p>Double.NaN is returned if no values have been added. * * @return the mean */ @Override public double getMean() { return _getMean().getResult(); }
private BigDecimal getMean(List<Double> data) { Mean mean = new Mean(); data.stream().forEach((value) -> mean.increment(value)); return BigDecimal.valueOf(mean.getResult()); }
static private Double evaluate(Collection<?> values){ Mean statistic = new Mean(); for(Object value : values){ Number number = (Number)TypeUtil.parseOrCast(DataType.DOUBLE, value); statistic.increment(number.doubleValue()); } return statistic.getResult(); } }
static private Double evaluate(Collection<?> values){ Mean statistic = new Mean(); for(Object value : values){ Double doubleValue = (Double)TypeUtil.parseOrCast(DataType.DOUBLE, value); statistic.increment(doubleValue.doubleValue()); } return statistic.getResult(); } }
static private Double evaluate(Collection<?> values){ Mean statistic = new Mean(); for(Object value : values){ Number number = (Number)TypeUtil.parseOrCast(DataType.DOUBLE, value); statistic.increment(number.doubleValue()); } return statistic.getResult(); } }