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
Project details
Release history Release notifications | RSS feed
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 |