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have an associated weight vs nodes have an associated weight

Both phrases are correct, but they are used in different contexts. 'Have an associated weight' can be used when the subject is clear or has been previously mentioned, while 'nodes have an associated weight' is more specific and suitable when referring to nodes in a particular context.

Last updated: March 19, 2024 • 593 views

have an associated weight

This phrase is correct and can be used when the subject is clear or has been previously mentioned.

This phrase is suitable when the subject is known or when it has been established in the context.

Examples:

  • The items in the list have an associated weight.
  • Each element must have an associated weight for the calculation to be accurate.
  • Each joint will have an associated weight map created based on the 'Bind Type' and its settings. Next, a series of Deform Influences are assigned to each joint of  ...
  • Oct 6, 2014 ... ... this is because every item in the second column(tags) needs to have an associated weight in the last column(number of users who annotated ...
  • Oct 31, 2014 ... Each process should have an associated weight that determines its proportional share allocation of processor time allocated in units of a time.
  • Nov 1, 2006 ... ... of the graph have an associated weight, then a maximum (minimum) weighted assignment is an assignment such that the sum of the weights ...

Alternatives:

  • possess an associated weight
  • carry an associated weight
  • include an associated weight
  • come with an associated weight
  • feature an associated weight

nodes have an associated weight

This phrase is also correct and is more specific, suitable when referring to nodes in a particular context.

This phrase is appropriate when explicitly talking about nodes and their associated weights.

Examples:

  • In the graph, nodes have an associated weight that influences the shortest path calculation.
  • Each node in the network has an associated weight assigned to it.
  • These nodes have an associated weight, n, that is the higher order variance for the mixture type it represents. For instance the three way mixture variance is.
  • Therefore each of the J hidden nodes have an associated weight vector wj ( single column of the Kohonen weight matrix, w) comprising I components. Likewise ...
  • ting two nodes have an associated weight that measures the distance to each partial candidate solution to the received vector. The addition of all the branch ...
  • Nodes have an associated weight representing the amount of computation required to execute the corresponding task, and edges have an as- sociated weight ...

Alternatives:

  • nodes possess an associated weight
  • nodes carry an associated weight
  • nodes include an associated weight
  • nodes come with an associated weight
  • nodes feature an associated weight

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