are values on the Edges. Weights can signify various things depending on the context. For example, weights on a directed graph can represent the distance required to get from node A to B, […]
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BAE, Sammie, 2019. JavaScript Data Structures and Algorithms: An Introduction to Understanding and Implementing Core Data Structure and Algorithm Fundamentals. Berkeley, CA: Apress : Imprint: Apress. ISBN 978-1-4842-3988-9, p. 277.
Yes, that is correct. In the context of a Neural Network, the weights on the edges between neurons represent the strength of the connections between those neurons. These weights are typically initialized randomly and then adjusted during the training process in order to optimize the network's performance.
In other contexts, such as a Directed Graph, weights on the edges can represent different things. For example, in a graph that represents a Transportation Network, the weights on the edges could represent the distance or time required to travel between two nodes. In a graph that represents a social network, the weights on the edges could represent the strength of the relationship between two individuals.