org.lenskit.eval.traintest.recommend

Class TopNMAPMetric

java.lang.Object

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

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

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

org.lenskit.eval.traintest.recommend.TopNMAPMetric

public class TopNMAPMetric
extends ListOnlyTopNMetric<TopNMAPMetric.Context>

Compute the mean average precision.

The algorithm computed here is equivalent to Ben Hammer’s Python implementation, as referenced by Kaggle.

This metric is registered under the name map. 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	TopNMAPMetric.AggregateResult
static class	TopNMAPMetric.Context
static class	TopNMAPMetric.UserResult

Constructor Summary

Constructors

Constructor and Description
TopNMAPMetric() Construct a new MAP metric with the user’s test items as good.
TopNMAPMetric(ItemSelector good, java.lang.String sfx) Construct a new mean average precision top n metric
TopNMAPMetric(PRMetricSpec spec) Create a metric from a spec.

Method Summary

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

TopNMAPMetric

public TopNMAPMetric()

Construct a new MAP metric with the user’s test items as good.

TopNMAPMetric

public TopNMAPMetric(PRMetricSpec spec)

Create a metric from a spec.

Parameters:

spec - The specification.

TopNMAPMetric

public TopNMAPMetric(ItemSelector good,
                     java.lang.String sfx)

Construct a new mean average precision top n metric

Parameters:

sfx - the suffix label for this evaluation, or null for no suffix.

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

Method Detail

createContext

@Nullable
public TopNMAPMetric.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<TopNMAPMetric.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(TopNMAPMetric.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<TopNMAPMetric.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 recs,
                                         TopNMAPMetric.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<TopNMAPMetric.Context>

Parameters:

rec - The recommender used to recommend for this user.

user - The user.

targetLength - The target list length.

recs - The list of recommendations.

context - The context.

Returns:

The results of measuring this user.