shchur / overlapping-community-detection Goto Github PK

Hello author, how did you get X in the Facebook dataset? The feature dimension of each ego-network is different from the original dataset.

N - node
M - edge
D - ?
C - community number?

am I right?

Notebook JSON is invalid: 'ename' is a required property
Could you specify the version of jupyter notebook you use?

Hi, I am trying to reproduce the best results of mag_cs dataset which achieves 50.2 in the paper. I adopt the same settings and early_stop as mentioned in your paper, but my best result achieved is 46.0 and generally the NMI score is around 43;
Besides, the weight_decay value in interactive.ipynb is 1e-5 by default while in your paper the regularization strength lambda=1e-2(which resulted poor performance). Which one should I use to reproduce the best result of CS dataset?

any suggestions?

Hi, I have read yoru code and have some questions here:

1. you adopted the self-implemented l2_reg_loss and add it to BP loss. Why don't you use the l2_reg of Adam optimizer by setting weight_decay param?
2. in your gcn implementation, I noticed
   
   I wonder why are there two dropout in one layer?

Hi, I recently read your paper,I‘m very interested in your paper,Can you provide comparison experiment code?For example,I I reproduced the result of Bigclam method is very low（ NMI=0.05.But the result you get is NMI=0.26）So I am very curious about what I did wrong.Thank you very much

In the nocd/sampler.py
to_keep = (1 - self.A[cne1, cne2]).astype(np.bool).A1 * (cne1 != cne2)

What is A1 here this is causing Error

Hi, @shchur
Would you please let me know the data format of the input graphs? I convert several graphs from mtx to npz, but the following errors occurred.
'
Traceback (most recent call last):
File "example.py", line 14, in
G = nocd.utils.load_dataset(path_to_dataset)
File "/home/community/nocd/nocd/utils.py", line 49, in load_dataset
A = sp.csr_matrix((loader['adj_data'], loader['adj_indices'],
KeyError: 'adj_data'
'

Hi Oleksandr,

Thanks for creating an excellent Jupyter notebook to accompany this interesting work! I was hoping to test this out, but am unfamiliar with the .npz input format used. I was wondering if you could provide a code snippet to utilize your method when starting with a NetworkX graph constructed from a simple edge list.

For example starting with graph from:

import networkx as nx
import pandas as pd

edges = pd.read_csv("Edge_List.csv")
graph = nx.from_pandas_edgelist(edges, "Source", "Target")

Thank you!
Steve

Hi, I converted the notebook into py but I got this error when running the code:

RuntimeError:
An attempt has been made to start a new process before the
current process has finished its bootstrapping phase.

Do you have any idea of what's causing it?