Skip to content

wakame1367/OptCAT

Repository files navigation

OptCAT

Actions Status Actions Status License: MIT

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 optcat

Testing

poetry run pytest

About

OptCAT (= Optuna + CatBoost)

Topics

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages