Algorithms

This section covers migration for all algorithms in the Neo4j Graph Data Science library.

1. Betweenness Centrality

Table 1. Changes in YIELD fields
1.x 2.x

minimumScore

Use centralityDistribution.min

maximumScore

Use centralityDistribution.max

scoreSum

No direct equivalent. For mean, use centralityDistribution.mean.

2. Breadth First Search

Table 2. Changes in configuration
1.x 2.x

String relationshipWeightProperty

Removed

startNodeId

sourceNode

Table 3. Changes in YIELD fields
1.x 2.x

startNodeId

sourceNode

3. Closeness Centrality

Table 4. Changes in algorithm configuration parameter map
1.x 2.x

improve

useWassermanFaust

Table 5. Changes in stream mode YIELD fields
1.x 2.x

centrality

score

Table 6. Changes in write mode YIELD fields
1.x 2.x

nodes

nodePropertiesWritten

-

configuration

4. Depth First Search

Table 7. Changes in configuration
1.x 2.x

String relationshipWeightProperty

Removed

startNodeId

sourceNode

Table 8. Changes in YIELD fields
1.x 2.x

startNodeId

sourceNode

5. K-Nearest Neighbors

Table 9. Changes in configuration
1.x 2.x

String nodeWeightProperty

String or Map or List of Strings / Maps nodeProperties

6. Alpha similarity algorithms

The alpha similarity procedures have been removed. Use KNN or Node Similarity instead. The similarity metrics for these can now be configured.

Knn

Cosine, Euclidean, Jaccard, Overlap, Pearson

Node Similarity

Jaccard, Overlap

The alpha similarity functions have been promoted to product tier.

1.x 2.x

gds.alpha.similarity.cosine

gds.similarity.cosine

gds.alpha.similarity.euclidean

gds.similarity.euclidean

gds.alpha.similarity.euclideanDistance

gds.similarity.euclideanDistance

gds.alpha.similarity.jaccard

gds.similarity.jaccard

gds.alpha.similarity.overlap

gds.similarity.overlap

gds.alpha.similarity.pearson

gds.similarity.pearson