🔥aizoo🔥
Install
pip install aizoo -U
Docs
Usages
OOF models
from aizoo.tab.models import TabNetClassifier
from sklearn.datasets import make_regression, make_classification
from sklearn.metrics import r2_score, roc_auc_score
X, y = make_classification(n_samples=10000)
TabNetClassifier().run(X, y, feval=roc_auc_score)
Hyperparameter optimization: search_space
from aizoo.tuner.optimizers import LGBOptimizer, F1Optimizer
from sklearn.datasets import make_regression, make_classification
X, y = make_classification(n_samples=1000)
opt = LGBOptimizer('search_space.yaml', X, y)
best_params = opt.optimize(100)
opt.plot()
TODO
======= History
0.0.0 (2021-09-04)
- First release on PyPI.
1 maintainer
Metadata
1 maintainer
Release files for aizoo 2022.11.1.17.47.51
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| aizoo-2022.11.1.17.47.51.tar.gz | 57.9 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| aizoo-2022.11.1.17.47.51-py2.py3-none-any.whl | Python 2, Python 3 | none | any | Details |
Total release size: 116.0 MB
Release files / aizoo-2022.11.1.17.47.51.tar.gz
| Download URL | aizoo-2022.11.1.17.47.51.tar.gz |
|---|---|
| Size | 57.9 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.1 CPython/3.9.7
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Release files / aizoo-2022.11.1.17.47.51-py2.py3-none-any.whl
| Download URL | aizoo-2022.11.1.17.47.51-py2.py3-none-any.whl |
|---|---|
| Size | 58.0 MB |
| Tags | Python 2 Python 3 |
|
SHA-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.1 CPython/3.9.7
|
