Comments (2)
Hi @chkoar, thank you for the feedback.
Sorry for the delay. I was away from the office because I attended a school and conference in the last weeks.
We are work in this feature now :)
We have a lot of complexity measure implemented in this branch: https://github.com/ealcobaca/pymfe/blob/complexity/pymfe/complexity.py
Other complexity measures will be added in the next weeks.
My suggestion, if you have time, is to check if we do not miss any complexity measure and if they are well implemented.
Feel free to contribute. You are always welcome :D
Best regards
Edesio
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Some papers are showing that complexity measures could be good meta-features
Agree. I am interested in implementing these meta-fuatures. I was going to build a separate package for that but since you have build a nice package around meta-features it would be a nice contribution.
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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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