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[9.0] [ML] RegressionIT: Fix hyperparameters for regression tests and unmute the test (#135541) #135771

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Oct 1, 2025
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[9.0] [ML] RegressionIT: Fix hyperparameters for regression tests and unmute the test (#135541) #135771

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53 changes: 25 additions & 28 deletions ...node-tests/src/javaRestTest/java/org/elasticsearch/xpack/ml/integration/RegressionIT.java
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Original file line number Diff line number Diff line change
Expand Up @@ -27,12 +27,8 @@
import org.elasticsearch.xpack.core.ml.dataframe.analyses.BoostedTreeParams;
import org.elasticsearch.xpack.core.ml.dataframe.analyses.Regression;
import org.elasticsearch.xpack.core.ml.inference.TrainedModelConfig;
import org.elasticsearch.xpack.core.ml.inference.TrainedModelDefinition;
import org.elasticsearch.xpack.core.ml.inference.preprocessing.OneHotEncoding;
import org.elasticsearch.xpack.core.ml.inference.preprocessing.PreProcessor;
import org.elasticsearch.xpack.core.ml.inference.trainedmodel.ensemble.Ensemble;
import org.elasticsearch.xpack.core.ml.inference.trainedmodel.metadata.Hyperparameters;
import org.elasticsearch.xpack.core.ml.inference.trainedmodel.metadata.TrainedModelMetadata;
import org.hamcrest.Matchers;
import org.junit.After;

Expand Down Expand Up @@ -540,7 +536,6 @@ public void testWithDatastream() throws Exception {
);
}

@AwaitsFix(bugUrl = "https://github.com/elastic/elasticsearch/issues/93228")
public void testAliasFields() throws Exception {
// The goal of this test is to assert alias fields are included in the analytics job.
// We have a simple dataset with two integer fields: field_1 and field_2.
Expand Down Expand Up @@ -585,10 +580,32 @@ public void testAliasFields() throws Exception {
// Very infrequently this test may fail as the algorithm underestimates the
// required number of trees for this simple problem. This failure is irrelevant
// for non-trivial real-world problem and improving estimation of the number of trees
// would introduce unnecessary overhead. Hence, to reduce the noise from this test we fix the seed.
// would introduce unnecessary overhead. Hence, to reduce the noise from this test we fix the seed
// and use the hyperparameters that are known to work.
long seed = 1000L; // fix seed

Regression regression = new Regression("field_2", BoostedTreeParams.builder().build(), null, 90.0, seed, null, null, null, null);
Regression regression = new Regression(
"field_2",
BoostedTreeParams.builder()
.setDownsampleFactor(0.7520841625652861)
.setAlpha(547.9095715556235)
.setLambda(3.3008189603590044)
.setGamma(1.6082763366825203)
.setSoftTreeDepthLimit(4.733224114945455)
.setSoftTreeDepthTolerance(0.15)
.setEta(0.12371209659057758)
.setEtaGrowthRatePerTree(1.0618560482952888)
.setMaxTrees(30)
.setFeatureBagFraction(0.8)
.build(),
null,
90.0,
seed,
null,
null,
null,
null
);
DataFrameAnalyticsConfig config = new DataFrameAnalyticsConfig.Builder().setId(jobId)
.setSource(new DataFrameAnalyticsSource(new String[] { sourceIndex }, null, null, Collections.emptyMap()))
.setDest(new DataFrameAnalyticsDest(destIndex, null))
Expand All @@ -604,19 +621,6 @@ public void testAliasFields() throws Exception {

waitUntilAnalyticsIsStopped(jobId);

// obtain addition information for investigation of #90599
String modelId = getModelId(jobId);
TrainedModelMetadata modelMetadata = getModelMetadata(modelId);
assertThat(modelMetadata.getHyperparameters().size(), greaterThan(0));
StringBuilder hyperparameters = new StringBuilder(); // used to investigate #90599
for (Hyperparameters hyperparameter : modelMetadata.getHyperparameters()) {
hyperparameters.append(hyperparameter.hyperparameterName).append(": ").append(hyperparameter.value).append("\n");
}
TrainedModelDefinition modelDefinition = getModelDefinition(modelId);
Ensemble ensemble = (Ensemble) modelDefinition.getTrainedModel();
int numberTrees = ensemble.getModels().size();

StringBuilder targetsPredictions = new StringBuilder(); // used to investigate #90599
assertResponse(prepareSearch(sourceIndex).setSize(totalDocCount), sourceData -> {
double predictionErrorSum = 0.0;
for (SearchHit hit : sourceData.getHits()) {
Expand All @@ -629,19 +633,12 @@ public void testAliasFields() throws Exception {
int featureValue = (int) destDoc.get("field_1");
double predictionValue = (double) resultsObject.get(predictionField);
predictionErrorSum += Math.abs(predictionValue - 2 * featureValue);

// collect the log of targets and predictions for debugging #90599
targetsPredictions.append(2 * featureValue).append(", ").append(predictionValue).append("\n");
}
// We assert on the mean prediction error in order to reduce the probability
// the test fails compared to asserting on the prediction of each individual doc.
double meanPredictionError = predictionErrorSum / sourceData.getHits().getHits().length;
String str = "Failure: failed for seed %d inferenceEntityId %s numberTrees %d\n";
assertThat(
Strings.format(str, seed, modelId, numberTrees) + targetsPredictions + hyperparameters,
meanPredictionError,
lessThanOrEqualTo(3.0)
);
assertThat(meanPredictionError, lessThanOrEqualTo(3.0));
});

assertProgressComplete(jobId);
Expand Down