Comments (4)
sir,
I want to use costcla library on my datasets as I am importing from costcla import models I am facing error that no module of sklearn.cross_validation. As it present in sklearn.model_selection. please help me to uses this package on my datasets
from costsensitiveclassification.
The code repository has been updated to work with sklearn.model_selection but it has not been pushed to pypi . To use the code :
- Clone the repository to your local environment .
- cd CostSensitiveClassification
- pip install .
You should be able to use the latest version of the code . A few minor changes may be required to make to tutorial notebook work .
from costsensitiveclassification.
You need to change the sentense in Anaconda3\Lib\site-packages\costcla-0.5-py3.7.egg\costcla\models, open cost_ensemble.py. Then change [from sklearn.cross_validation import train_test_split] to [sklearn.model_selection import train_test_split]
from costsensitiveclassification.
Done. Sorry for the delay
from costsensitiveclassification.
Related Issues (20)
- multiclass classification example?
- Push to PyPi HOT 2
- `load_bankmarketing` no longer works HOT 2
- Update example notebook to work with latest version of sklearn HOT 1
- Update tutorial link in README HOT 1
- I want to draw a cost-sensitive decision tree, but it has an error. HOT 1
- Imbalanced Dataset vs Cost Function HOT 3
- costcla incompatible with latest version of Scikit-Learn HOT 6
- Visualize features being used by CostSensitiveDecisionTreeClassifier HOT 1
- Calculation of cost saving HOT 2
- Cannot use predict_proba with cost matrix ?
- pyea imports
- Problem with imports from pyea HOT 3
- getting error: 'bool' object has no attribute 'astype'
- ModuleNotFoundError HOT 2
- Cost sensitive Decision Tree predict the same value HOT 1
- Imbalanced prediction on obesity datasets using cost sensitive algorithms??
- ModuleNotFoundError: No module named 'sklearn.externals.joblib'
- Add a Conda Forge Package
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from costsensitiveclassification.