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/*
* Copyright Elasticsearch B.V. and/or licensed to Elasticsearch B.V. under one
* or more contributor license agreements. Licensed under the Elastic License
* 2.0; you may not use this file except in compliance with the Elastic License
* 2.0.
*/
package org.elasticsearch.xpack.core.ml.dataframe.evaluation;
import org.elasticsearch.common.ParseField;
import org.elasticsearch.common.io.stream.NamedWriteableRegistry;
import org.elasticsearch.common.xcontent.NamedXContentRegistry;
import org.elasticsearch.plugins.spi.NamedXContentProvider;
import org.elasticsearch.xpack.core.ml.dataframe.evaluation.classification.Accuracy;
import org.elasticsearch.xpack.core.ml.dataframe.evaluation.classification.AucRoc;
import org.elasticsearch.xpack.core.ml.dataframe.evaluation.classification.Classification;
import org.elasticsearch.xpack.core.ml.dataframe.evaluation.classification.MulticlassConfusionMatrix;
import org.elasticsearch.xpack.core.ml.dataframe.evaluation.classification.Precision;
import org.elasticsearch.xpack.core.ml.dataframe.evaluation.classification.Recall;
import org.elasticsearch.xpack.core.ml.dataframe.evaluation.common.AbstractAucRoc;
import org.elasticsearch.xpack.core.ml.dataframe.evaluation.outlierdetection.ConfusionMatrix;
import org.elasticsearch.xpack.core.ml.dataframe.evaluation.outlierdetection.OutlierDetection;
import org.elasticsearch.xpack.core.ml.dataframe.evaluation.outlierdetection.ScoreByThresholdResult;
import org.elasticsearch.xpack.core.ml.dataframe.evaluation.regression.Huber;
import org.elasticsearch.xpack.core.ml.dataframe.evaluation.regression.MeanSquaredError;
import org.elasticsearch.xpack.core.ml.dataframe.evaluation.regression.MeanSquaredLogarithmicError;
import org.elasticsearch.xpack.core.ml.dataframe.evaluation.regression.RSquared;
import org.elasticsearch.xpack.core.ml.dataframe.evaluation.regression.Regression;
import java.util.Arrays;
import java.util.List;
public class MlEvaluationNamedXContentProvider implements NamedXContentProvider {
/**
* Constructs the name under which a metric (or metric result) is registered.
* The name is prefixed with evaluation name so that registered names are unique.
*
* @param evaluationName name of the evaluation
* @param metricName name of the metric
* @return name appropriate for registering a metric (or metric result) in {@link NamedXContentRegistry}
*/
public static String registeredMetricName(ParseField evaluationName, ParseField metricName) {
return registeredMetricName(evaluationName.getPreferredName(), metricName.getPreferredName());
}
/**
* Constructs the name under which a metric (or metric result) is registered.
* The name is prefixed with evaluation name so that registered names are unique.
*
* @param evaluationName name of the evaluation
* @param metricName name of the metric
* @return name appropriate for registering a metric (or metric result) in {@link NamedXContentRegistry}
*/
public static String registeredMetricName(String evaluationName, String metricName) {
return evaluationName + "." + metricName;
}
@Override
public List getNamedXContentParsers() {
return Arrays.asList(
// Evaluations
new NamedXContentRegistry.Entry(Evaluation.class, OutlierDetection.NAME, OutlierDetection::fromXContent),
new NamedXContentRegistry.Entry(Evaluation.class, Classification.NAME, Classification::fromXContent),
new NamedXContentRegistry.Entry(Evaluation.class, Regression.NAME, Regression::fromXContent),
// Outlier detection metrics
new NamedXContentRegistry.Entry(EvaluationMetric.class,
new ParseField(
registeredMetricName(
OutlierDetection.NAME, org.elasticsearch.xpack.core.ml.dataframe.evaluation.outlierdetection.AucRoc.NAME)),
org.elasticsearch.xpack.core.ml.dataframe.evaluation.outlierdetection.AucRoc::fromXContent),
new NamedXContentRegistry.Entry(EvaluationMetric.class,
new ParseField(
registeredMetricName(
OutlierDetection.NAME, org.elasticsearch.xpack.core.ml.dataframe.evaluation.outlierdetection.Precision.NAME)),
org.elasticsearch.xpack.core.ml.dataframe.evaluation.outlierdetection.Precision::fromXContent),
new NamedXContentRegistry.Entry(EvaluationMetric.class,
new ParseField(
registeredMetricName(
OutlierDetection.NAME, org.elasticsearch.xpack.core.ml.dataframe.evaluation.outlierdetection.Recall.NAME)),
org.elasticsearch.xpack.core.ml.dataframe.evaluation.outlierdetection.Recall::fromXContent),
new NamedXContentRegistry.Entry(EvaluationMetric.class,
new ParseField(registeredMetricName(OutlierDetection.NAME, ConfusionMatrix.NAME)),
ConfusionMatrix::fromXContent),
// Classification metrics
new NamedXContentRegistry.Entry(EvaluationMetric.class,
new ParseField(registeredMetricName(Classification.NAME, AucRoc.NAME)),
AucRoc::fromXContent),
new NamedXContentRegistry.Entry(EvaluationMetric.class,
new ParseField(registeredMetricName(Classification.NAME, MulticlassConfusionMatrix.NAME)),
MulticlassConfusionMatrix::fromXContent),
new NamedXContentRegistry.Entry(EvaluationMetric.class,
new ParseField(registeredMetricName(Classification.NAME, Accuracy.NAME)),
Accuracy::fromXContent),
new NamedXContentRegistry.Entry(EvaluationMetric.class,
new ParseField(registeredMetricName(Classification.NAME, Precision.NAME)),
Precision::fromXContent),
new NamedXContentRegistry.Entry(EvaluationMetric.class,
new ParseField(registeredMetricName(Classification.NAME, Recall.NAME)),
Recall::fromXContent),
// Regression metrics
new NamedXContentRegistry.Entry(EvaluationMetric.class,
new ParseField(registeredMetricName(Regression.NAME, MeanSquaredError.NAME)),
MeanSquaredError::fromXContent),
new NamedXContentRegistry.Entry(EvaluationMetric.class,
new ParseField(registeredMetricName(Regression.NAME, MeanSquaredLogarithmicError.NAME)),
MeanSquaredLogarithmicError::fromXContent),
new NamedXContentRegistry.Entry(EvaluationMetric.class,
new ParseField(registeredMetricName(Regression.NAME, Huber.NAME)),
Huber::fromXContent),
new NamedXContentRegistry.Entry(EvaluationMetric.class,
new ParseField(registeredMetricName(Regression.NAME, RSquared.NAME)),
RSquared::fromXContent)
);
}
public static List getNamedWriteables() {
return Arrays.asList(
// Evaluations
new NamedWriteableRegistry.Entry(Evaluation.class,
OutlierDetection.NAME.getPreferredName(),
OutlierDetection::new),
new NamedWriteableRegistry.Entry(Evaluation.class,
Classification.NAME.getPreferredName(),
Classification::new),
new NamedWriteableRegistry.Entry(Evaluation.class,
Regression.NAME.getPreferredName(),
Regression::new),
// Evaluation metrics
new NamedWriteableRegistry.Entry(EvaluationMetric.class,
registeredMetricName(
OutlierDetection.NAME, org.elasticsearch.xpack.core.ml.dataframe.evaluation.outlierdetection.AucRoc.NAME),
org.elasticsearch.xpack.core.ml.dataframe.evaluation.outlierdetection.AucRoc::new),
new NamedWriteableRegistry.Entry(EvaluationMetric.class,
registeredMetricName(
OutlierDetection.NAME, org.elasticsearch.xpack.core.ml.dataframe.evaluation.outlierdetection.Precision.NAME),
org.elasticsearch.xpack.core.ml.dataframe.evaluation.outlierdetection.Precision::new),
new NamedWriteableRegistry.Entry(EvaluationMetric.class,
registeredMetricName(
OutlierDetection.NAME, org.elasticsearch.xpack.core.ml.dataframe.evaluation.outlierdetection.Recall.NAME),
org.elasticsearch.xpack.core.ml.dataframe.evaluation.outlierdetection.Recall::new),
new NamedWriteableRegistry.Entry(EvaluationMetric.class,
registeredMetricName(OutlierDetection.NAME, ConfusionMatrix.NAME),
ConfusionMatrix::new),
new NamedWriteableRegistry.Entry(EvaluationMetric.class,
registeredMetricName(Classification.NAME, AucRoc.NAME),
AucRoc::new),
new NamedWriteableRegistry.Entry(EvaluationMetric.class,
registeredMetricName(Classification.NAME, MulticlassConfusionMatrix.NAME),
MulticlassConfusionMatrix::new),
new NamedWriteableRegistry.Entry(EvaluationMetric.class,
registeredMetricName(Classification.NAME, Accuracy.NAME),
Accuracy::new),
new NamedWriteableRegistry.Entry(EvaluationMetric.class,
registeredMetricName(Classification.NAME, Precision.NAME),
Precision::new),
new NamedWriteableRegistry.Entry(EvaluationMetric.class,
registeredMetricName(Classification.NAME, Recall.NAME),
Recall::new),
new NamedWriteableRegistry.Entry(EvaluationMetric.class,
registeredMetricName(Regression.NAME, MeanSquaredError.NAME),
MeanSquaredError::new),
new NamedWriteableRegistry.Entry(EvaluationMetric.class,
registeredMetricName(Regression.NAME, MeanSquaredLogarithmicError.NAME),
MeanSquaredLogarithmicError::new),
new NamedWriteableRegistry.Entry(EvaluationMetric.class,
registeredMetricName(Regression.NAME, Huber.NAME),
Huber::new),
new NamedWriteableRegistry.Entry(EvaluationMetric.class,
registeredMetricName(Regression.NAME, RSquared.NAME),
RSquared::new),
// Evaluation metrics results
new NamedWriteableRegistry.Entry(EvaluationMetricResult.class,
registeredMetricName(OutlierDetection.NAME, ScoreByThresholdResult.NAME),
ScoreByThresholdResult::new),
new NamedWriteableRegistry.Entry(EvaluationMetricResult.class,
registeredMetricName(OutlierDetection.NAME, ConfusionMatrix.NAME),
ConfusionMatrix.Result::new),
new NamedWriteableRegistry.Entry(EvaluationMetricResult.class,
AbstractAucRoc.Result.NAME,
AbstractAucRoc.Result::new),
new NamedWriteableRegistry.Entry(EvaluationMetricResult.class,
registeredMetricName(Classification.NAME, MulticlassConfusionMatrix.NAME),
MulticlassConfusionMatrix.Result::new),
new NamedWriteableRegistry.Entry(EvaluationMetricResult.class,
registeredMetricName(Classification.NAME, Accuracy.NAME),
Accuracy.Result::new),
new NamedWriteableRegistry.Entry(EvaluationMetricResult.class,
registeredMetricName(Classification.NAME, Precision.NAME),
Precision.Result::new),
new NamedWriteableRegistry.Entry(EvaluationMetricResult.class,
registeredMetricName(Classification.NAME, Recall.NAME),
Recall.Result::new),
new NamedWriteableRegistry.Entry(EvaluationMetricResult.class,
registeredMetricName(Regression.NAME, MeanSquaredError.NAME),
MeanSquaredError.Result::new),
new NamedWriteableRegistry.Entry(EvaluationMetricResult.class,
registeredMetricName(Regression.NAME, MeanSquaredLogarithmicError.NAME),
MeanSquaredLogarithmicError.Result::new),
new NamedWriteableRegistry.Entry(EvaluationMetricResult.class,
registeredMetricName(Regression.NAME, Huber.NAME),
Huber.Result::new),
new NamedWriteableRegistry.Entry(EvaluationMetricResult.class,
registeredMetricName(Regression.NAME, RSquared.NAME),
RSquared.Result::new)
);
}
}
