Comments (2)
eliorc
commented on May 20, 2024
- Outputs of node2vec are for all nodes in the graph, you can't filter out nodes, unless you make the walk probability to/from them to zero, which is equivalent to just removing them from the graph.
- Much like word2vec only learns embeddings for words it has seen and treats unmet words as OOV, you can try to take the same approach
from node2vec.
AmalNammouchi
commented on May 20, 2024
when I add a node to my graph which has no link on it (it s like a new node that still has no link), and then apply node2vec to my graph and check the most similar nodes to my node, it outputs some results, but I am not sure according to what exactly it outputed that result, according to what those outputed nodes are similar to my unconnected node?
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Related Issues (20)
- How can node2vec use GPU HOT 1
- too slow and stuck for some reason HOT 9
- reproducability HOT 2
- failing simple clustering of synthetic networks HOT 2
- Error in model creation node2vec HOT 1
- Cannot import Node2Vec HOT 5
- A faster implement HOT 1
- Train vs Inference methods HOT 6
- [Question] about directed graph and weight HOT 2
- There may be a small problem with the walking length. HOT 1
- Interpretation of weights HOT 2
- model save and loading examples HOT 2
- Are there any ways to initialize node vector using pretrained embeddings? HOT 1
- Crash when edges are not initialised with a weight attribute HOT 8
- can same temp directory be used for different graphs in for loop training? HOT 4
- _precompute_probabilities parallel execution HOT 2
- import error HOT 3
- segmentation fault HOT 5
- Error installing gensim in poetry env on mac m1 HOT 3
- How to set parameters for a collection small disconnected graphs HOT 2
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