Improve wording and use static imports

Co-authored-by: Jacob Sznajdman <breakanalysis@gmail.com>

Author: FlorentinD

doc/asciidoc/machine-learning/node-property-prediction/noderegression-pipeline/config.adoc

@@ -2,19 +2,19 @@
 = Configuring the pipeline
 :max-trials: 10
 
-This page explains how to create and configure a node classification pipeline.
+This page explains how to create and configure a node regression pipeline.
 It consists of the following sections:
 
-* <<nodregression-creating-a-pipeline, Creating the pipeline>>
+* <<noderegression-creating-a-pipeline, Creating the pipeline>>
 
 
-[[nodregression-creating-a-pipeline]]
+[[noderegression-creating-a-pipeline]]
 == Creating a pipeline
 
 The first step of building a new pipeline is to create one using `gds.alpha.pipeline.nodeRegression.create`.
 This stores a trainable pipeline object in the pipeline catalog of type `Node regression training pipeline`.
 This represents a configurable pipeline that can later be invoked for training, which in turn creates a regression model.
-The latter is also a model which is stored in the catalog with type `NodeRegression`.
+The latter is a model which is stored in the catalog with type `NodeRegression`.
 
 
 === Syntax

proc/machine-learning/src/main/java/org/neo4j/gds/ml/pipeline/node/classification/predict/NodeClassificationPipelineMutateProc.java

@@ -47,8 +47,10 @@
 
 import static org.neo4j.gds.executor.ExecutionMode.MUTATE_NODE_PROPERTY;
 import static org.neo4j.gds.ml.PipelineCompanion.prepareTrainConfig;
+import static org.neo4j.gds.ml.pipeline.node.classification.NodeClassificationPipelineCompanion.ESTIMATE_PREDICT_DESCRIPTION;
+import static org.neo4j.gds.ml.pipeline.node.classification.NodeClassificationPipelineCompanion.PREDICT_DESCRIPTION;
 
-@GdsCallable(name = "gds.beta.pipeline.nodeClassification.predict.mutate", description = org.neo4j.gds.ml.pipeline.node.classification.NodeClassificationPipelineCompanion.PREDICT_DESCRIPTION, executionMode = MUTATE_NODE_PROPERTY)
+@GdsCallable(name = "gds.beta.pipeline.nodeClassification.predict.mutate", description = PREDICT_DESCRIPTION, executionMode = MUTATE_NODE_PROPERTY)
 public class NodeClassificationPipelineMutateProc
     extends MutatePropertyProc<
     NodeClassificationPredictPipelineExecutor,
@@ -57,7 +59,7 @@ public class NodeClassificationPipelineMutateProc
     NodeClassificationPredictPipelineMutateConfig>
 {
     @Procedure(name = "gds.beta.pipeline.nodeClassification.predict.mutate", mode = Mode.READ)
-    @Description(org.neo4j.gds.ml.pipeline.node.classification.NodeClassificationPipelineCompanion.PREDICT_DESCRIPTION)
+    @Description(PREDICT_DESCRIPTION)
     public Stream<MutateResult> mutate(
         @Name(value = "graphName") String graphName,
         @Name(value = "configuration", defaultValue = "{}") Map<String, Object> configuration
@@ -67,7 +69,7 @@ public Stream<MutateResult> mutate(
     }
 
     @Procedure(name = "gds.beta.pipeline.nodeClassification.predict.mutate.estimate", mode = Mode.READ)
-    @Description(org.neo4j.gds.ml.pipeline.node.classification.NodeClassificationPipelineCompanion.ESTIMATE_PREDICT_DESCRIPTION)
+    @Description(ESTIMATE_PREDICT_DESCRIPTION)
     public Stream<MemoryEstimateResult> estimate(
         @Name(value = "graphNameOrConfiguration") Object graphNameOrConfiguration,
         @Name(value = "algoConfiguration") Map<String, Object> algoConfiguration
@@ -98,7 +100,7 @@ protected List<NodeProperty> nodePropertyList(ComputationResult<NodeClassificati
         var nodeProperties = new ArrayList<NodeProperty>();
         nodeProperties.add(NodeProperty.of(mutateProperty, classProperties));
 
-        result.predictedProbabilities().ifPresent((probabilityProperties) -> {
+        result.predictedProbabilities().ifPresent(probabilityProperties -> {
             var properties = new DoubleArrayNodePropertyValues() {
                 @Override
                 public long size() {

proc/machine-learning/src/main/java/org/neo4j/gds/ml/pipeline/node/classification/predict/NodeClassificationPipelineStreamProc.java

@@ -49,13 +49,14 @@
 import static org.neo4j.gds.ml.PipelineCompanion.prepareTrainConfig;
 import static org.neo4j.gds.ml.pipeline.node.classification.NodeClassificationPipelineCompanion.ESTIMATE_PREDICT_DESCRIPTION;
 import static org.neo4j.gds.ml.pipeline.node.classification.NodeClassificationPipelineCompanion.PREDICT_DESCRIPTION;
+import static org.neo4j.gds.ml.pipeline.node.classification.predict.NodeClassificationPipelineStreamProc.NodeClassificationStreamResult;
 
 @GdsCallable(name = "gds.beta.pipeline.nodeClassification.predict.stream", description = PREDICT_DESCRIPTION, executionMode = STREAM)
 public class NodeClassificationPipelineStreamProc
     extends StreamProc<
     NodeClassificationPredictPipelineExecutor,
     NodeClassificationPredict.NodeClassificationResult,
-    NodeClassificationPipelineStreamProc.NodeClassificationStreamResult,
+    NodeClassificationStreamResult,
     NodeClassificationPredictPipelineStreamConfig>
 {
 
@@ -96,7 +97,7 @@ protected Stream<NodeClassificationStreamResult> stream(
             return LongStream
                 .range(0, graph.nodeCount())
                 .boxed()
-                .map((nodeId) ->
+                .map(nodeId ->
                     new NodeClassificationStreamResult(
                         graph.toOriginalNodeId(nodeId),
                         predictedClasses.get(nodeId),
@@ -106,7 +107,7 @@ protected Stream<NodeClassificationStreamResult> stream(
         });
     }
 
-    private List<Double> nodePropertiesAsList(Optional<HugeObjectArray<double[]>> predictedProbabilities, long nodeId) {
+    private static List<Double> nodePropertiesAsList(Optional<HugeObjectArray<double[]>> predictedProbabilities, long nodeId) {
         return predictedProbabilities.map(p -> {
             var values = p.get(nodeId);
             return Arrays.stream(values).boxed().collect(Collectors.toList());