Comments (1)
@seanM29 the weights of edges would be greater when they are directed and form loops, its just an output of the way clustering equation is implemented, however important to know is that FICNH does not use any edge weights, they may as well be all set to 1's (I leave this out to save some compute.. as it doesn't matter we just use all connected components irrespective of their weights). The comparison of min_sim is only optional (see the updated read me), it helps early exit and may prove useful when your data is unbalanced. This however also can not be done when you are using approx NN (KD-tree) to find the 1st nbr, only would run when using exact distance to compute 1st nbrs.
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Related Issues (20)
- features for Hollywood and MPII Cooking 2 HOT 1
- The code for TW-FINCH is not available
- TWFinch code missing FS "Eval" option; unable to reproduce accuracy HOT 1
- errors when run the run_on_dataset.m HOT 8
- There is a bug when using pynndescent.NNDescent HOT 2
- ValueError: all the input arrays must have same number of dimensions, but the array at index 0 has 4 dimensions(s) and the array at index 1 has 2 deminesion (s). HOT 1
- TW-FINCH feature extraction method HOT 1
- Is there any randomness in the clustering results? HOT 1
- element of adjacent matrix may greater than 1 HOT 4
- Different Clustering results when using python and matlab implementation HOT 2
- Finch Algo 2
- Segmentation fault for large dataset of 5M datapoints of 1024 dimensions HOT 1
- Unable to replicate numbers HOT 1
- TWFinch code missing YTI without 75% background option; unable to reproduce accuracy HOT 5
- Replace `sklearn` with `scikit-learn` in `setup.py` HOT 1
- If the way F1-scores is calculated is different in matlab and python HOT 3
- How to get the midpoint hit criterion for the MPII? HOT 1
- `sklearn` is still a dependency in `setup.py` HOT 1
- IndexError when req_clust > num_clust HOT 5
- Error when runninng TW_FINCH and specifying the number of clusters.
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