graph-data-science
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Source code for the Neo4j Graph Data Science library of graph algorithms.
I have an in-memory graph created using the gds.graph.create() procedure. I want to add a property to some of the nodes in the graph. Simply setting the properties of those...
In the [documentation](https://neo4j.com/docs/graph-data-science/current/management-ops/graph-catalog-ops/), there is no API that allows us to query a named graph. The reason for this feature is that given a Neo4j graph, we project into a...
Currently, there is no option to define which nodes you want to use for items and which ones you want to use for the weights part of the algorithm. By...
**Describe the bug** **To Reproduce** GDS version: 2.1.12 Neo4j Desktop version: 1.4.15 Operating system: Windows 10 Steps to reproduce the behavior: - [1] Create the database Fraud Risk Prevention -...
**Is your feature request related to a problem? Please describe.** I am using the Louvain algorithm to discover communities in my graph; however, each execution of the algorithm returns different...
**Is your feature request related to a problem? Please describe.** The objective is to find, in the database, frequent paths or relevant paths based on its nodes. **Describe the solution...
**Problem** - I have a trained GraphSage model. - Consider a constant graph, nothing changes across runs. However, running `gds.beta.graphSage.stream` (or `gds.beta.graphSage.mutate`) yields inconsistent embeddings for the same node between...
The compatibility matrix table headers are mixed up, this MR fixes it.
**Describe the bug** Link prediction operations (e.g., `.create`, `.addNodeProperty`) fail, using GDS 2.5.1 and 2.5.3. **To Reproduce** A. Execute either of these using the Python GDS client: - `pipe =...
If I am not wrong; after reading the [Making recommendations](https://neo4j.com/docs/graph-data-science/current/end-to-end-examples/fastrp-knn-example/#_making_recommendations) paragraph, it looks like the query does make predictions correctly but for opposite order of people(nodes) in the graph. This...