org.lenskit.eval.traintest.predict

Class MAEPredictMetric

java.lang.Object

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

org.lenskit.eval.traintest.predict.PredictMetric<MAEPredictMetric.Context>

org.lenskit.eval.traintest.predict.MAEPredictMetric

public class MAEPredictMetric
extends PredictMetric<MAEPredictMetric.Context>

Evaluate a recommender’s prediction accuracy with MAE (Mean Absolute Error).

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
class	MAEPredictMetric.Context

Constructor Summary

Constructors

Constructor and Description
MAEPredictMetric()

Method Summary

Modifier and Type	Method and Description
MAEPredictMetric.Context	createContext(AlgorithmInstance algorithm, DataSet dataSet, RecommenderEngine engine) Create the context for an experimental condition (algorithm/data set pair).
MetricResult	getAggregateMeasurements(MAEPredictMetric.Context context) Get the aggregate results from an accumulator.
MetricResult	measureUser(TestUser user, ResultMap predictions, MAEPredictMetric.Context context) Measure a single result.

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

MAEPredictMetric

public MAEPredictMetric()

Method Detail

createContext

@Nullable
public MAEPredictMetric.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<MAEPredictMetric.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.

measureUser

@Nonnull
public MetricResult measureUser(TestUser user,
                                         ResultMap predictions,
                                         MAEPredictMetric.Context context)

Description copied from class: PredictMetric

Measure a single result. The result may come from either prediction or recommendation.

Thread Safety: This method may be called concurrently by multiple threads with the same recommender and context.

Specified by:

measureUser in class PredictMetric<MAEPredictMetric.Context>

Parameters:

user - The user’s test data.

predictions - The predictions.

Returns:

A list of fields to add to the result’s output.

getAggregateMeasurements

@Nonnull
public MetricResult getAggregateMeasurements(MAEPredictMetric.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<MAEPredictMetric.Context>

Parameters:

context - The context for an experimental condition.

Returns:

The aggregate results from the accumulator.