org.lenskit.eval.traintest.recommend

Class TopNNDCGMetric

java.lang.Object

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

org.lenskit.eval.traintest.recommend.TopNMetric<X>

org.lenskit.eval.traintest.recommend.ListOnlyTopNMetric<org.apache.commons.math3.stat.descriptive.moment.Mean>

org.lenskit.eval.traintest.recommend.TopNNDCGMetric

public class TopNNDCGMetric
extends ListOnlyTopNMetric<org.apache.commons.math3.stat.descriptive.moment.Mean>

Measure the nDCG of the top-N recommendations, using ratings as scores.

This metric is registered with the type name ndcg.

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	TopNNDCGMetric.Spec Specification for configuring nDCG metrics.

Field Summary

Fields

Modifier and Type	Field and Description
static java.lang.String	DEFAULT_COLUMN

Constructor Summary

Constructors

Constructor and Description
TopNNDCGMetric() Create an nDCG metric with log-2 discounting.
TopNNDCGMetric(Discount disc) Create an nDCG metric with a default name.
TopNNDCGMetric(Discount disc, java.lang.String name) Construct a new nDCG Top-N metric.
TopNNDCGMetric(Discount disc, java.lang.String name, java.lang.String attr) Construct a new nDCG Top-N metric.
TopNNDCGMetric(TopNNDCGMetric.Spec spec) Construct a top-N nDCG metric from a spec.

Method Summary

Modifier and Type	Method and Description
org.apache.commons.math3.stat.descriptive.moment.Mean	createContext(AlgorithmInstance algorithm, DataSet dataSet, RecommenderEngine engine) Create the context for an experimental condition (algorithm/data set pair).
MetricResult	getAggregateMeasurements(org.apache.commons.math3.stat.descriptive.moment.Mean context) Get the aggregate results from an accumulator.
MetricResult	measureUser(Recommender rec, TestUser user, int targetLength, LongList recommendations, org.apache.commons.math3.stat.descriptive.moment.Mean context) Measurement method that only uses the recommend list.

Methods inherited from class org.lenskit.eval.traintest.recommend.ListOnlyTopNMetric

measureUser

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

getAggregateColumnLabels, getColumnLabels, getRequiredRoots

Methods inherited from class java.lang.Object

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

Field Detail

DEFAULT_COLUMN

public static final java.lang.String DEFAULT_COLUMN

See Also:

Constant Field Values

Constructor Detail

TopNNDCGMetric

public TopNNDCGMetric()

Create an nDCG metric with log-2 discounting.

TopNNDCGMetric

public TopNNDCGMetric(Discount disc)

Create an nDCG metric with a default name.

Parameters:

disc - The discount to apply.

TopNNDCGMetric

public TopNNDCGMetric(TopNNDCGMetric.Spec spec)

Construct a top-N nDCG metric from a spec.

Parameters:

spec - The spec.

TopNNDCGMetric

public TopNNDCGMetric(Discount disc,
                      java.lang.String name)

Construct a new nDCG Top-N metric.

Parameters:

disc - The discount to apply.

name - The column name to use.

TopNNDCGMetric

public TopNNDCGMetric(Discount disc,
                      java.lang.String name,
                      java.lang.String attr)

Construct a new nDCG Top-N metric.

Parameters:

disc - The discount to apply.

name - The column name to use.

Method Detail

createContext

@Nullable
public org.apache.commons.math3.stat.descriptive.moment.Mean createContext(AlgorithmInstance algorithm,
                                                                                     DataSet dataSet,
                                                                                     RecommenderEngine engine)

Description copied from class: Metric

Create the context for an experimental condition (algorithm/data set pair). The default implementation returns null.

Note: Contexts must be thread-safe, in that multiple concurrent calls to the appropriate user-measurement function with the same context must be safe. This can be handled either by the context itself, or by the user-measurement function.

Overrides:

createContext in class Metric<org.apache.commons.math3.stat.descriptive.moment.Mean>

Parameters:

algorithm - The algorithm.

dataSet - The data set.

engine - The LensKit recommender engine, if applicable. This can be null for an external algorithm that does not provide a LensKit recommender.

Returns:

The context. This will be passed to the individual measurement methods. If the metric does need to accumulate any results, this method can return null.

getAggregateMeasurements

@Nonnull
public MetricResult getAggregateMeasurements(org.apache.commons.math3.stat.descriptive.moment.Mean context)

Description copied from class: Metric

Get the aggregate results from an accumulator. The default implementation returns MetricResult.empty().

Overrides:

getAggregateMeasurements in class Metric<org.apache.commons.math3.stat.descriptive.moment.Mean>

Parameters:

context - The context for an experimental condition.

Returns:

The aggregate results from the accumulator.

measureUser

@Nonnull
public MetricResult measureUser(Recommender rec,
                                         TestUser user,
                                         int targetLength,
                                         LongList recommendations,
                                         org.apache.commons.math3.stat.descriptive.moment.Mean context)

Description copied from class: ListOnlyTopNMetric

Measurement method that only uses the recommend list.

Thread Safety: This method may be called concurrently by multiple threads with the same recommender and context.

Specified by:

measureUser in class ListOnlyTopNMetric<org.apache.commons.math3.stat.descriptive.moment.Mean>

Parameters:

rec - The recommender used to recommend for this user.

user - The user.

targetLength - The target list length.

recommendations - The list of recommendations.

context - The context.

Returns:

The results of measuring this user.