Skip to main content

Sci-kit learn tools for machine learning pipelines

Project description

scikit-duplo

Very simple reusable blocks for scikit-learn pipelines (inspired by scikit-lego)

License: MIT PyPI Documentation Status

Installation

Installation from the source tree:

python setup.py install

Or via pip from PyPI:

pip install scikit-duplo

Contents

The sci-kit duplo package contains multiple classes that you can use in a sci-kit learn compatible pipeline. There are ensemble learning classes within the meta subdirectory. These classes expect you to pass in multiple other Sci-kit learn compatible machine learning classes. It will use these to build an ensemble of models to predict the target variable.

There are feature engineering classes inside the preprocessing subdirectory. These are ColumnTransformer compatible classes that expect to receive a dataframe and set of column names that it will transform for the downstream pipeline processes.

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

skduplo-0.1.1.tar.gz (2.8 kB view details)

Uploaded Source

File details

Details for the file skduplo-0.1.1.tar.gz.

File metadata

  • Download URL: skduplo-0.1.1.tar.gz
  • Upload date:
  • Size: 2.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.16

File hashes

Hashes for skduplo-0.1.1.tar.gz
Algorithm Hash digest
SHA256 5e2892e2f2aebfc84df027746a3769e2f9a0584f3032aaf4d852d75c0e1a21f3
MD5 3599ac46e3495a6113e67da42a2af8c9
BLAKE2b-256 62d68d8f920a8b1fc6e45f27afbd87596356135785b59f4ec8549766e57832a5

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