How is graph theory applied in machine learning?

How is graph theory applied in machine learning?

Graph theory is used in machine learning to model relationships between data points, enabling better understanding and predictions.

Can you give an example of a machine learning algorithm that uses graph theory?

Sure! One example is the Graph Neural Network (GNN), which processes data structured as graphs to learn representations.

What are the benefits of using graph theory in machine learning?

Using graph theory helps capture complex relationships, improves data representation, and enhances model performance.

Are there any limitations to using graph theory in machine learning?

Yes, some limitations include computational complexity and the need for large amounts of data to effectively train models.