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vtraag / louvain-igraph

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How to exactly handle negative weights?

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tjiagoM
tjiagoM commented May 18, 2018

I started using louvain-igraph because of the possibility of using negative weights in community detection. However, I think your documentation is not very clear in some points and if possible I would like some clarification. Maybe I just misunderstood some parts.

  1. First, regarding the attribute consider_comms. From what I understood, I just needed to set this attribute (for example in `Mod
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Splitter

benedekrozemberczki / Splitter

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A Pytorch implementation of "Splitter: Learning Node Representations that Capture Multiple Social Contexts" (WWW 2019).

machine-learning deep-learning clustering word2vec community-detection pytorch deepwalk gensim factorization network-embedding node2vec graph-embedding overlapping-community-detection deep-neural-network graph-representation-learning node-embedding implicit-factorization graph-neural-network ego-splitting word-vector
  • Updated Apr 1, 2020
  • Python
EgoSplitting

benedekrozemberczki / EgoSplitting

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A NetworkX implementation of "Ego-splitting Framework: from Non-Overlapping to Overlapping Clusters" (KDD 2017).

machine-learning deep-learning clustering machine-learning-algorithms community-detection networkx kdd community-detection-algorithm igraph graph-clustering louvain-algorithm fuzzy-clustering ego-network louvain-community-detection louvain-method community-detection-evaluation ego-networks graph-clustering-algorithm fast-clustering persona-graph
  • Updated May 31, 2020
  • Python

benedekrozemberczki / LabelPropagation

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A NetworkX implementation of Label Propagation from a "Near Linear Time Algorithm to Detect Community Structures in Large-Scale Networks" (Physical Review E 2008).

community graph clustering community-detection dataset graph-cut modularity louvain unsupervised-learning propagation graph-partitioning label-propagation graph-clustering fast-greedy randomized-algorithm homophily walktrap probabilistic-clustering
  • Updated Apr 1, 2020
  • Python

wiheto / teneto

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Error in tutorial : inconsistent TemporalNetwork.network type?

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maximelucas
maximelucas commented Mar 6, 2020

Copy pasting the first few lines of the tutorial
https://teneto.readthedocs.io/en/latest/tutorial/networkrepresentation.html#temporalnetwork-object
yields an error at tnet.network.head() because tnet created with
tnet.generatenetwork('rand_binomial',size=(5,3), prob=0.5)
is a Numpy ndarray and not a Pandas DataFrame.

I haven't tried other ways of creating tnet, so I'm not sure if `t

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