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Co-Authored-By: Adam Schill Collberg <adam.schill.collberg@protonmail.com>
Co-Authored-By: Mats Rydberg <mats.rydberg@neotechnology.com>

Author: 3 people

algo/src/main/java/org/neo4j/gds/embeddings/hashgnn/BinarizeFeaturesConfig.java

@@ -23,7 +23,7 @@
 import org.neo4j.gds.annotation.Configuration;
 
 import java.util.Collection;
-import java.util.Collections;
+import java.util.List;
 import java.util.Map;
 
 @Configuration
@@ -47,7 +47,7 @@ default Map<String, Object> toMap() {
     @Value.Default
     @Value.Parameter(false)
     default Collection<String> configKeys() {
-        return Collections.emptyList();
+        return List.of();
     }
 
 }

algo/src/main/java/org/neo4j/gds/embeddings/hashgnn/GenerateFeaturesConfig.java

@@ -23,7 +23,7 @@
 import org.neo4j.gds.annotation.Configuration;
 
 import java.util.Collection;
-import java.util.Collections;
+import java.util.List;
 import java.util.Map;
 
 import static org.neo4j.gds.utils.StringFormatting.formatWithLocale;
@@ -47,7 +47,7 @@ default Map<String, Object> toMap() {
     @Value.Default
     @Value.Parameter(false)
     default Collection<String> configKeys() {
-        return Collections.emptyList();
+        return List.of();
     }
 
     @Value.Check

doc/modules/ROOT/partials/machine-learning/node-embeddings/hashgnn/specific-configuration.adoc

@@ -4,6 +4,6 @@
 | heterogeneous                                                                    | Boolean         | false           | yes       | Whether different relationship types should be treated differently.
 | neighborInfluence                                                                | Float           | 1.0             | yes       | Controls how often neighbors' features are sampled in each iteration relative to sampling the node's own features. Must be non-negative.
 | binarizeFeatures                                                                 | Map             | n/a             | yes       | A map with keys `dimension` and `threshold`. If given, features are transformed into `dimension` binary features via hyperplane rounding. Increasing `threshold` makes the output more sparse, and it defaults to `0`. The value of `dimension` must be at least 1.
-| generateFeatures                                                                 | Map             | n/a             | yes       | A map with keys `dimension` and `densityLevel`. Should be given if and only if `featureProperties` is empty. If given, `dimension` binary features are generated with approximately `densityLevel` active features per node. Both must be at least 1 and `densityLevel` at most `density`.
+| generateFeatures                                                                 | Map             | n/a             | yes       | A map with keys `dimension` and `densityLevel`. Should be given if and only if `featureProperties` is empty. If given, `dimension` binary features are generated with approximately `densityLevel` active features per node. Both must be at least 1 and `densityLevel` at most `dimension`.
 | outputDimension                                                                  | Integer         | n/a             | yes       | If given, the embeddings are projected randomly into `outputDimension` dense features. Must be at least 1.
 | randomSeed                                                                       | Integer         | n/a             | yes       | A random seed which is used for all randomness in computing the embeddings.