Comments (6)
Hi @jadermcs,
I'm working on your request.
Felipe.
from pymfe.
Hi @lorinczszabolcs,
this feature is now on the master branch.
Felipe.
from pymfe.
Thank you for suggesting this new feature @jadermcs
from pymfe.
Hi @ealcobaca ! Could you give an estimated time when the unsupervised feature will be added? Or is there anything with which we can help?
All the best,
Szabi
from pymfe.
Thank you very much!
Have a nice weekend,
Szabi
from pymfe.
Thank you @lorinczszabolcs and @FelSiq.
You can use this feature by installing our master version.
It will be in the PyPI as soon as possible.
Feel free to contribute. We will appreciate new clustering meta-feature.
If you wish to contribute, you could check if we miss some clustering meta-feature and provide its implementation to PyMFE.
Best regards :)
from pymfe.
Related Issues (20)
- [BUG] eigenvalue.mean outputing complex numbers HOT 3
- [BUG] `suppress_warnings` not suppressing all warnings HOT 3
- Method for extracting meta-feature names before extraction
- Enable parallel computation HOT 5
- Merge with ts-pymfe HOT 2
- Target variable HOT 3
- Online example for the method to extract meta-feature names before any extraction HOT 2
- MemoryError when use a large dataset [BUG] HOT 5
- [BUG] Many Feature-extraction improvement HOT 2
- New version 0.4.1
- [BUG] Online documentation example seems incorrect HOT 1
- Performance of Info-theoretic extraction
- [BUG] AttributeError in igraph.GraphBase.Weighted_Adjacency
- [BUG] Unable to run MFE for datasets of more than ~500 features HOT 2
- [BUG] nan value when complexity measure is calculated HOT 2
- numpy.linalg.LinAlgError: SVD did not converge HOT 1
- General + Statistical Metafeatures HOT 1
- Output structure HOT 5
- Support for regression tasks or issue an error while fitting real-valued 'y'
- New pymfe version - - 0.4 HOT 2
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