Skip to main content

Neptune.ai scikit-learn integration library

Project description

Neptune: sklearn integration

See the official docs.

Minimal example:

from sklearn.datasets import load_boston
from sklearn.ensemble import RandomForestRegressor
from sklearn.model_selection import train_test_split
import neptune.new as neptune
import neptune.new.integrations.sklearn as npt_utils

run = neptune.init(project='common/sklearn-integration',
                   api_token='ANONYMOUS',
                   name='regression-example',
                   tags=['RandomForestRegressor', 'regression'])

parameters = {'n_estimators': 70,
              'max_depth': 7,
              'min_samples_split': 3}


rfr = RandomForestRegressor(**parameters)

X, y = load_boston(return_X_y=True)
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.20, random_state=28743)

rfr.fit(X_train, y_train)

run['rfr_summary'] = npt_utils.create_regressor_summary(rfr, X_train, X_test, y_train, y_test)

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

neptune-sklearn-0.9.5.tar.gz (24.9 kB view hashes)

Uploaded Source

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