Comments (3)
would this be the equivalent of a .fit_transform() method though? If so I think it makes more sense in BaseEmbed
from graspologic.
It's an operation on the latent positions tho, not the embedding. Why do you think it should go in the embedding?
from graspologic.
I just want the estimated latent positions, which should be returned by calling fit_transform, similar to sklearn (e.g. with PCA, i can call .fit_transform() to fit it and get the transformed data out with one function call).
We can implement the operation in LPM and have fit_transform call that function, but I just want a shortcut.
from graspologic.
Related Issues (20)
- [BUG] Graph matching errors when similarity matrix has unequal dimensions
- Impossible to use, get error message AttributeError: module 'numpy' has no attribute 'object' [BUG] HOT 4
- Installing graspologic on M1 HOT 1
- [BUG] Error in `graph_match` with optimal transport HOT 10
- Ensure we have a non-dev-mode install of graspologic as part of CI/CD workflow
- Audit test warnings for deprecation warnings HOT 1
- [BUG] graspologic v.2.0.1 and networkx 3.0 incompatibility leads to a crash HOT 1
- [BUG] Following the first tutorial on the documentation, first example fails due to networkx HOT 2
- Add CITATION.cff file HOT 2
- MatplotlibDeprecationWarning to address
- Numpy DeprecationWarning to address HOT 1
- Sklearn FutureWarning to address
- [BUG] What does "Spectral Vertex Nomination" implement? HOT 1
- [BUG] graspologic takes 33 seconds to import HOT 9
- [BUG] The docs do not reflect the modification of the graph_match module HOT 1
- [BUG] Numba warnings
- The whole package works with numpy matrices; why doesn't node2vec? HOT 1
- [Question] coefficient magnitude, GCT HOT 5
- [Question] Running Leiden community detection on random graph generates multiple communities HOT 3
- [BUG] SBMEstimator throws an error when "loops=False" and some block has size 1
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