Skip to main content

Tools of sklearn. Grid Search with multiprocess

Project description

Usage Sample ''''''''''''

.. code:: python

import numpy as np
from sklearn.ensemble import RandomForestClassifier
from sklearn.model_selection import train_test_split
from sklearntools import train_evaluate, search_model_params

if __name__ == '__main__':
     X, y = np.arange(20).reshape((10, 2)), range(10)
     X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3)

     model = RandomForestClassifier(n_estimators=837, bootstrap=False)
     train_evaluate(model, X_train, X_test, y_train, y_test)

     param_grid = {'n_estimators': np.arange(800, 820, 1), 'bootstrap': [False, True]}
     search_model_params(RandomForestClassifier, X_train, X_test, y_train, y_test, param_grid, result_num=3)

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

sklearntools-1.2.3.tar.gz (4.6 kB view details)

Uploaded Source

File details

Details for the file sklearntools-1.2.3.tar.gz.

File metadata

  • Download URL: sklearntools-1.2.3.tar.gz
  • Upload date:
  • Size: 4.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.0 CPython/3.9.18

File hashes

Hashes for sklearntools-1.2.3.tar.gz
Algorithm Hash digest
SHA256 30b85a6df236e467a5ef85b775b9e30296f2d017c3676af90b8398767974bd7e
MD5 9ba2755a23611b1ec91501d1e57a6085
BLAKE2b-256 f9bf99707eddbbff46df0ed7a47b78e4b53b783faa63f3a8906ce6534bed31b8

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