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[9.1] [LTR] Fix feature display order when using explain. (#137671) #137686

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Merged
merged 1 commit into from
Nov 6, 2025
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[9.1] [LTR] Fix feature display order when using explain. (#137671) #137686

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5 changes: 5 additions & 0 deletions docs/changelog/137671.yaml
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Original file line number Diff line number Diff line change
@@ -0,0 +1,5 @@
pr: 137671
summary: "[LTR] Fix feature display order when using explain"
area: Search
type: bug
issues: []
36 changes: 17 additions & 19 deletions ...rc/javaRestTest/java/org/elasticsearch/xpack/ml/integration/LearningToRankRescorerIT.java
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Expand Up @@ -83,7 +83,7 @@ public void testLearningToRankRescoreWithExplain() throws Exception {
}
}""");
var response = client().performRequest(request);
assertExplainExtractedFeatures(response, List.of("type_tv", "cost", "two"));
assertExplainExtractedFeatures(response, List.of("cost", "type_tv", "two"));
}

public void testLearningToRankRescoreSmallWindow() throws Exception {
Expand Down Expand Up @@ -192,27 +192,25 @@ private static void assertExplainExtractedFeatures(Response response, List<Strin
assertThat(queryDetails.get(1).get("description"), equalTo("extracted features"));

var featureDetails = new ArrayList<>((ArrayList<Map<String, Object>>) queryDetails.get(1).get("details"));
assertThat(featureDetails.size(), equalTo(3));

var missingKeys = new ArrayList<String>();
for (String expectedFeature : expectedFeatures) {
var expectedDescription = Strings.format("feature value for [%s]", expectedFeature);

var wasFound = false;
for (Map<String, Object> detailItem : featureDetails) {
if (detailItem.get("description").equals(expectedDescription)) {
featureDetails.remove(detailItem);
wasFound = true;
break;
}
}

if (wasFound == false) {
missingKeys.add(expectedFeature);
assertThat(featureDetails.size(), equalTo(expectedFeatures.size()));

// Extract feature names in the order they appear in the explanation
List<String> actualFeatureOrder = new ArrayList<>();
for (Map<String, Object> detailItem : featureDetails) {
String description = (String) detailItem.get("description");
// Extract feature name from "feature value for [featureName]"
if (description != null && description.startsWith("feature value for [") && description.endsWith("]")) {
String featureName = description.substring("feature value for [".length(), description.length() - 1);
actualFeatureOrder.add(featureName);
}
}

assertThat(Strings.format("Could not find features: [%s]", String.join(", ", missingKeys)), featureDetails.size(), equalTo(0));
// Verify that features appear in the expected order
assertThat(
"Features should appear in the expected order. Expected: " + expectedFeatures + ", Actual: " + actualFeatureOrder,
actualFeatureOrder,
equalTo(expectedFeatures)
);
}
}

Expand Down
18 changes: 10 additions & 8 deletions ...gin/ml/src/main/java/org/elasticsearch/xpack/ml/inference/ltr/LearningToRankRescorer.java
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Expand Up @@ -28,7 +28,6 @@
import java.util.Comparator;
import java.util.List;
import java.util.Map;
import java.util.Objects;
import java.util.Set;

import static java.util.stream.Collectors.toUnmodifiableSet;
Expand Down Expand Up @@ -169,21 +168,24 @@ public Explanation explain(int topLevelDocId, IndexSearcher searcher, RescoreCon
List<FeatureExtractor> featureExtractors = ltrContext.buildFeatureExtractors(searcher);
int featureSize = featureExtractors.stream().mapToInt(fe -> fe.featureNames().size()).sum();

Map<String, Object> features = Maps.newMapWithExpectedSize(featureSize);
Map<String, Object> extractedFeatures = Maps.newMapWithExpectedSize(featureSize);

for (FeatureExtractor featureExtractor : featureExtractors) {
featureExtractor.setNextReader(currentSegment);
featureExtractor.addFeatures(features, targetDoc);
featureExtractor.addFeatures(extractedFeatures, targetDoc);
}

// Predicting the value
var ltrScore = ((Number) localModelDefinition.inferLtr(features, ltrContext.learningToRankConfig).predictedValue()).floatValue();
var ltrScore = ((Number) localModelDefinition.inferLtr(extractedFeatures, ltrContext.learningToRankConfig).predictedValue())
.floatValue();

List<Explanation> featureExplanations = new ArrayList<>();
for (String featureName : features.keySet()) {
Number featureValue = Objects.requireNonNullElse((Number) features.get(featureName), 0);
featureExplanations.add(Explanation.match(featureValue, "feature value for [" + featureName + "]"));
}
ltrContext.learningToRankConfig.getFeatureExtractorBuilders().forEach(featureExtractor -> {
String featureName = featureExtractor.featureName();
if (extractedFeatures.containsKey(featureName) && extractedFeatures.get(featureName) instanceof Number featureValue) {
featureExplanations.add(Explanation.match(featureValue, "feature value for [" + featureName + "]"));
}
});

return Explanation.match(
ltrScore,
Expand Down