Skip to main content

OptCAT (= Optuna + CatBoost) provides a scikit-learn compatible estimator that tunes hyperparameters in CatBoost with Optuna.

Project description

OptCAT

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 git+https://github.com/wakamezake/OptCAT.git

Testing

poetry run pytest

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

optcat-0.1.0.tar.gz (5.1 kB view details)

Uploaded Source

Built Distribution

OptCAT-0.1.0-py3-none-any.whl (5.2 kB view details)

Uploaded Python 3

File details

Details for the file optcat-0.1.0.tar.gz.

File metadata

  • Download URL: optcat-0.1.0.tar.gz
  • Upload date:
  • Size: 5.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.0.5 CPython/3.6.5 Windows/10

File hashes

Hashes for optcat-0.1.0.tar.gz
Algorithm Hash digest
SHA256 a1ea3955bcbc618ab2fae1861567bc581009780d12ad3f5ab3ceadabc74300c8
MD5 2206849a4d09efc10cb37019c13486b0
BLAKE2b-256 ec72a80bf0dd74cfd3c8830af663014e6c86140c1f50e48877b70193e85a6107

See more details on using hashes here.

File details

Details for the file OptCAT-0.1.0-py3-none-any.whl.

File metadata

  • Download URL: OptCAT-0.1.0-py3-none-any.whl
  • Upload date:
  • Size: 5.2 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.0.5 CPython/3.6.5 Windows/10

File hashes

Hashes for OptCAT-0.1.0-py3-none-any.whl
Algorithm Hash digest
SHA256 680595e07d64350831679e7e75bdace7c03e90354de7f10902e34544f443611c
MD5 fd1300f28a57a425a61a624a54c243b6
BLAKE2b-256 02f2d80b96ebafb1a831b9e7123ee5d893b3b012649aeacd202d8be91d0cf0b8

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page