Comments (4)
Hi @GDGauravDutta :
Thanks for testing out featurewiz 👍
I have only two API's for featurewiz: Both of them now work the same using the same underlying algorithms.
The reason the two API's exist is that the old API is still in use among many researchers. The new API is in use among new researchers and students. So I didn't want to disadvantage one group vs. another.
But their inner workings are the same. Is there a reason you are not happy with one vs. another? Can you please expliain more here?
Thanks
Auto Vimal
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Issue like in available documentation. I have used kaggle as a platform for the last 3 months, I am getting lots of errors with solov. I understand the importance of both. I would like to have both formats used so as we can say it works the same and can help the community with our feedback.
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As an end user, I love to experiment with new ideas & Library. I found your repo with my quick experiment.
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Hi @GDGauravDutta
You mentioned " I am getting lots of errors with solov."
Can you point me links to your Kagge notebooks where you are getting errors with Sulov? I'd like to take a look and troubleshoot if I can.
Thanks
Auto Vimal
from featurewiz.
Related Issues (20)
- Category type, indexes don't match on AutoEncoding HOT 3
- Issue with working with Featureviz HOT 1
- Comment has incorrect code ( verbose=0. imbalanced=False [verbose=0, imbalanced=False]) HOT 1
- make tensorflow optional HOT 4
- lazytransform.py float to integer error HOT 2
- Dealing with a Numpy array as features HOT 1
- Convert binary columns to categorical HOT 1
- featurewiz ignores category columns HOT 2
- dont show chart for more than 1000 features HOT 1
- featurewiz ignores category columns with an example HOT 5
- wiz.tarnsform returns the same data as the train for test HOT 1
- package versions have conflicting dependencies HOT 1
- TypeError: expected string or bytes-like object on int type column name HOT 2
- Conflict Error Among Poetry Package Dependencies: lazytransform, tqdm, featurewiz HOT 8
- TYPO ERROR
- Typo Error
- Version Conflict for scikit-learn - Bump to 1.3.2 possible? HOT 1
- Can't get featurewiz to work HOT 1
- ValueError: Length mismatch: Expected axis has X elements, new values have Y elements HOT 3
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