org.lenskit.eval.traintest.metrics

Class ResultMetric<X>

java.lang.Object

org.lenskit.eval.traintest.metrics.Metric<X>

org.lenskit.eval.traintest.metrics.ResultMetric<X>

public abstract class ResultMetric<X>
extends Metric<X>

Base class for metrics that measure individual recommendation or prediction results.

Constructor Summary

Constructors

Modifier	Constructor and Description
protected	ResultMetric(java.lang.Class<? extends TypedMetricResult> resType, java.lang.Class<? extends TypedMetricResult> aggType) Construct a new result metric.
protected	ResultMetric(java.util.List<java.lang.String> labels, java.util.List<java.lang.String> aggLabels) Construct a new result metric.

Method Summary

Modifier and Type	Method and Description
abstract MetricResult	measureResult(long userId, Result result, X context) Measure a single result.

Methods inherited from class org.lenskit.eval.traintest.metrics.Metric

createContext, getAggregateColumnLabels, getAggregateMeasurements, getColumnLabels, getRequiredRoots

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

ResultMetric

protected ResultMetric(java.util.List<java.lang.String> labels,
                       java.util.List<java.lang.String> aggLabels)

Construct a new result metric.

Parameters:

labels - Column labels.

aggLabels - Aggregate column labels.

ResultMetric

protected ResultMetric(java.lang.Class<? extends TypedMetricResult> resType,
                       java.lang.Class<? extends TypedMetricResult> aggType)

Construct a new result metric.

Parameters:

resType - The result type for measuring results, or null for no measurement.

aggType - The result type for aggregate measurements, or null for no measurement.

Method Detail

measureResult

@Nonnull
public abstract MetricResult measureResult(long userId,
                                                    Result result,
                                                    X context)

Measure a single result. The result may come from either prediction or recommendation.

Parameters:

userId - The user ID.

result - The result to measure.

Returns:

A list of fields to add to the result’s output.