Skip to main content

Hyper Paramter Tuning and Models performance comparison

Project description

onepiecepredictor Package

pip install onepiecepredictor

A Small package for hyper paramter tuning pipelining and comparing multiple models performance with very little code.

Its a wrapper around sklearn, xgboost, catboost, imblearn packages.

For examples and documentation, please check Refer to this notebook

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

onepiecepredictor-1.2.tar.gz (6.3 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

onepiecepredictor-1.2-py3-none-any.whl (10.7 kB view details)

Uploaded Python 3

File details

Details for the file onepiecepredictor-1.2.tar.gz.

File metadata

  • Download URL: onepiecepredictor-1.2.tar.gz
  • Upload date:
  • Size: 6.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/49.2.0.post20200714 requests-toolbelt/0.9.1 tqdm/4.47.0 CPython/3.8.3

File hashes

Hashes for onepiecepredictor-1.2.tar.gz
Algorithm Hash digest
SHA256 ab784926460a9e6e423c7aff2b16f6b408d7282cb37bfa8c7344d1576c45cc3a
MD5 af9d166ef3838096cdb57f1f277ceeb3
BLAKE2b-256 c1a21db3cd2b46bd5b0aaf909d94d86b57d861223dda056923c185959de73954

See more details on using hashes here.

File details

Details for the file onepiecepredictor-1.2-py3-none-any.whl.

File metadata

  • Download URL: onepiecepredictor-1.2-py3-none-any.whl
  • Upload date:
  • Size: 10.7 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/49.2.0.post20200714 requests-toolbelt/0.9.1 tqdm/4.47.0 CPython/3.8.3

File hashes

Hashes for onepiecepredictor-1.2-py3-none-any.whl
Algorithm Hash digest
SHA256 623e1eebc6f092e34eff3754716511fdf5297283dbc5bbd492a7ac0b0e4cdb71
MD5 ef081aa8a2239d0f8386105c68296ccc
BLAKE2b-256 8e5a5a69ab5c06eaa4f4fc7b54e59745f97337c4d2e27cc098338e1e1fc04e6b

See more details on using hashes here.

Supported by

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