public class TopNNDPMMetric extends ListOnlyTopNMetric<org.apache.commons.math3.stat.descriptive.moment.Mean>
Measure the nDPM of the top-N recommendations, using rankings. This metric is registered with the type name ndpm. The paper used as a reference for this implementation is http://www2.cs.uregina.ca/~yyao/PAPERS/jasis_ndpm.pdf.
| Modifier and Type | Class and Description |
|---|---|
static class |
TopNNDPMMetric.Spec
Specification for configuring nDPM metrics.
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| Modifier and Type | Field and Description |
|---|---|
static java.lang.String |
DEFAULT_COLUMN |
| Constructor and Description |
|---|
TopNNDPMMetric(java.lang.String name)
Construct a new nDPM Top-N metric.
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TopNNDPMMetric(TopNNDPMMetric.Spec spec)
Construct a top-N nDCG metric from a spec.
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| 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.
|
measureUsergetAggregateColumnLabels, getColumnLabels, getRequiredRootspublic static final java.lang.String DEFAULT_COLUMN
public TopNNDPMMetric(TopNNDPMMetric.Spec spec)
Construct a top-N nDCG metric from a spec.
spec - The spec.public TopNNDPMMetric(java.lang.String name)
Construct a new nDPM Top-N metric.
@Nullable public org.apache.commons.math3.stat.descriptive.moment.Mean createContext(AlgorithmInstance algorithm, DataSet dataSet, RecommenderEngine engine)
MetricCreate 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.
createContext in class Metric<org.apache.commons.math3.stat.descriptive.moment.Mean>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.null.@Nonnull public MetricResult getAggregateMeasurements(org.apache.commons.math3.stat.descriptive.moment.Mean context)
MetricGet the aggregate results from an accumulator. The default implementation returns MetricResult.empty().
getAggregateMeasurements in class Metric<org.apache.commons.math3.stat.descriptive.moment.Mean>context - The context for an experimental condition.@Nonnull public MetricResult measureUser(Recommender rec, TestUser user, int targetLength, LongList recommendations, org.apache.commons.math3.stat.descriptive.moment.Mean context)
ListOnlyTopNMetricMeasurement method that only uses the recommend list.
Thread Safety: This method may be called concurrently by multiple threads with the same recommender and context.
measureUser in class ListOnlyTopNMetric<org.apache.commons.math3.stat.descriptive.moment.Mean>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.