Comments (1)
VHRanger
commented on August 18, 2024
1
Hey,
I also answered in the PR, but it was a temporary deployment issue. Sorry for that, managing multi-package github deployment is new to me.
Everything should be stable now (I added tests so CI shouldn't pass if it happens again). This is the major release for the time being.
Additionally, umap is missing from the requirements.
UMAP shouldn't be a dependency for this if possible. It's only used in the notebook examples because it's one of the better uses for SKLearnEmbedder.
I really appreciate the work you've put into this package, when I was looking for a node2vec implementation many months ago yours was by far the cleanest and fastest. Thanks!
Happy to hear that! Hopefully you enjoy the new features like reading in large graphs without using networkX and the new algorithms. ProNE and GGVec especially are very good alternatives to node2vec for large graphs!
from nodevectors.
Related Issues (20)
- Embedding a VERY LARGE graph, upcoming? HOT 2
- When saving large graph, creating a temporary folder will cause the system disk resources to be exhausted. HOT 1
- Issue with gensim 4.0.0+ HOT 3
- is it possible to split n2v to generate walks only? HOT 4
- node2vec uses CBOW instead of skip-gram HOT 4
- Setting value of seed to make Node2vec embedding repeatable. HOT 1
- Print training progression (node2vec)? HOT 1
- Continue fitting process HOT 2
- Has node2vec implementation been updated to use skip-gram as default? HOT 3
- About painting HOT 1
- defining random state or seed option parameters HOT 3
- Why is generating walks so slow with non-default parameters? HOT 3
- word2vec parameters changed HOT 3
- Problem with underlying Word2vec HOT 1
- G.mat got an asymmetric sparse matrix
- ProNE option: "inconsistent shapes" error
- Node2Vec:About the return_weight and neighbor_weight
- ProNE multithread HOT 1
- NetworkX 3.0 remove adj_matrix in version HOT 1
- Old parameter shows up in Word2Vec call
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