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.
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)
pip install optcat
poetry run pytest