Graph Classification
The short answer · 9 words
In short
Graph classification assigns a class to a complete graph.
Flow-alerta.cab (2026): Graph Classification. https://flow-alerta.cab/en/glossar/graph-classification. Editorially reviewed on: 10 October 2026.
How much detail would you like?
Practical
Relevant for molecules, process graphs or network states, provided there are sufficient comparable graphs.
Hypothetical example: Process graphs are classified according to stable and error-prone sequence patterns.
Check whether your cases are meaningful as whole graphs and enough independent labels are available.
At a glance
- Core
- Prediction unit is the entire graph. In GNN methods, node representations are combined to form a graph representation via a readout function. Graph features or graph cores are also possible. A continuous target value belongs to the graph regression.
- Use
- Relevant for molecules, process graphs or network states, provided there are sufficient comparable graphs.
- Example
- Hypothetical example: Process graphs are classified according to stable and error-prone sequence patterns.
- Limits
- Mix node and graph splits; leak similar substructures over data sets; use graph size as a shortcut.
In context
Questions about this term
What is the prediction unit?
The entire graph.
Do you need GNNs?
No, graph cores or features are also possible.
All details and background
Prediction unit is the entire graph. In GNN methods, node representations are combined to form a graph representation via a readout function. Graph features or graph cores are also possible. A continuous target value belongs to the graph regression.
ELI5 – Explained simply
The model evaluates an entire network instead of individual points.
Why it matters in practice
Relevant for molecules, process graphs or network states, provided there are sufficient comparable graphs.
Example
Hypothetical example: Process graphs are classified according to stable and error-prone sequence patterns.
Pitfalls and limits
- Mix node and graph splits; leak similar substructures over data sets; use graph size as a shortcut.
Origin & history
Graph classification evolved from graph cores and later GNN-based representations.
Use in mid-sized companies
- Check whether your cases are meaningful as whole graphs and enough independent labels are available.
Related terms
- GNN
- Readout
- Graph kernels
- Node classification
- GIN
Matching Flow-alerta service
AI opportunity analysis & roadmapAI consulting: Examine tasks, data and prerequisites of a possible AI use case.Matching tool / use case
View use casesGraph features or graph cores; GNN with graph-wide readout function; graph split evaluation.Sources
Quellenprüfung: 10.10.2026. Definition und dokumentierte Einordnung abgeglichen; Beispiele beschreiben mögliche Anwendungen.
Editorially reviewed on: