OptCAT (= Optuna + CatBoost) provides a scikit-learn compatible estimator that tunes hyperparameters in CatBoost with Optuna.
Project description
OptCAT
OptCAT (= Optuna + CatBoost) provides a scikit-learn compatible estimator that tunes hyperparameters in CatBoost with Optuna.
This Repository is very influenced by Y-oHr-N/OptGBM.
Examples
from optcat.core import CatBoostClassifier
from sklearn import datasets
params = {
"bootstrap_type": "Bayesian",
"loss_function": "Logloss",
"iterations": 100
}
model = CatBoostClassifier(params=params, n_trials=5)
data, target = datasets.load_breast_cancer(return_X_y=True)
model.fit(X=data, y=target)
Installation
pip install git+https://github.com/wakamezake/OptCAT.git
Testing
poetry run pytest
Release history Release notifications
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
| Filename, size | File type | Python version | Upload date | Hashes |
|---|---|---|---|---|
| Filename, size OptCAT-0.1.0-py3-none-any.whl (5.2 kB) | File type Wheel | Python version py3 | Upload date | Hashes View |
| Filename, size optcat-0.1.0.tar.gz (5.1 kB) | File type Source | Python version None | Upload date | Hashes View |
