org.lenskit.eval.traintest.recommend

Class TopNEntropyMetric

java.lang.Object

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

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

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

org.lenskit.eval.traintest.recommend.TopNEntropyMetric

public class TopNEntropyMetric
extends ListOnlyTopNMetric<TopNEntropyMetric.Context>

Metric that measures the entropy of the top N recommendations across all users.

This tell us essentially how large of a range of the items your recommender is covering. It does not return any per-user results.

Small values indicate that the algorithm tends to prefer a small number of items which it recomments to all users. Large values mean that the algorithm recommends many different items (to many different users)

The smallest value happens when the topN list is the same for all users (which would give an entropy of roughly log_2(N)). The largest value happens when each item is recommended the same number of times (for an entropy of roughly log_2(number of items)).

This metric is registered with the type name entropy.

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	TopNEntropyMetric.Context
static class	TopNEntropyMetric.EntropyResult

Constructor Summary

Constructors

Constructor and Description
TopNEntropyMetric() Construct a new length metric.

Method Summary

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

TopNEntropyMetric

public TopNEntropyMetric()

Construct a new length metric.

Method Detail

measureUser

@Nonnull
public MetricResult measureUser(Recommender rec,
                                         TestUser user,
                                         int targetLength,
                                         LongList recommendations,
                                         TopNEntropyMetric.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<TopNEntropyMetric.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.

createContext

@Nullable
public TopNEntropyMetric.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<TopNEntropyMetric.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(TopNEntropyMetric.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<TopNEntropyMetric.Context>

Parameters:

context - The context for an experimental condition.

Returns:

The aggregate results from the accumulator.