org.lenskit.eval.traintest.recommend

Class TopNMRRMetric

java.lang.Object

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

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

org.lenskit.eval.traintest.recommend.ListOnlyTopNMetric<TopNMRRMetric.Context>

org.lenskit.eval.traintest.recommend.TopNMRRMetric

public class TopNMRRMetric
extends ListOnlyTopNMetric<TopNMRRMetric.Context>

Compute the mean reciprocal rank.

This metric is registered with the type name mrr. It has two configuration parameters:

suffix

a suffix to append to the column name

goodItems

an item selector expression. The default is the user’s test items.

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	TopNMRRMetric.AggregateResult
static class	TopNMRRMetric.Context
static class	TopNMRRMetric.UserResult

Constructor Summary

Constructors

Constructor and Description
TopNMRRMetric() Construct a new MRR metric using the user’s test items as good.
TopNMRRMetric(ItemSelector goodItems, java.lang.String sfx) Construct a new recall and precision top n metric
TopNMRRMetric(PRMetricSpec spec) Construct an MRR metric from a spec.

Method Summary

Modifier and Type	Method and Description
TopNMRRMetric.Context	createContext(AlgorithmInstance algorithm, DataSet dataSet, RecommenderEngine engine) Create the context for an experimental condition (algorithm/data set pair).
MetricResult	getAggregateMeasurements(TopNMRRMetric.Context context) Get the aggregate results from an accumulator.
MetricResult	measureUser(Recommender rec, TestUser user, int targetLength, LongList recommendations, TopNMRRMetric.Context 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

Constructor Detail

TopNMRRMetric

public TopNMRRMetric()

Construct a new MRR metric using the user’s test items as good.

TopNMRRMetric

public TopNMRRMetric(PRMetricSpec spec)

Construct an MRR metric from a spec.

Parameters:

spec - The metric specl

TopNMRRMetric

public TopNMRRMetric(ItemSelector goodItems,
                     java.lang.String sfx)

Construct a new recall and precision top n metric

Parameters:

goodItems - The list of items to consider “true positives”, all other items will be treated as “false positives”.

sfx - A suffix to append to the metric.

Method Detail

createContext

@Nullable
public TopNMRRMetric.Context 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<TopNMRRMetric.Context>

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(TopNMRRMetric.Context context)

Description copied from class: Metric

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

Overrides:

getAggregateMeasurements in class Metric<TopNMRRMetric.Context>

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,
                                         TopNMRRMetric.Context 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<TopNMRRMetric.Context>

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.