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 |
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static class |
TopNNDPMMetric.Spec
Specification for configuring nDPM metrics.
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Modifier and Type | Field and Description |
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static java.lang.String |
DEFAULT_COLUMN |
Constructor and Description |
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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 |
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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.
|
measureUser
getAggregateColumnLabels, getColumnLabels, getRequiredRoots
public 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)
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.
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)
Metric
Get 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)
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.
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.