Skip to main content

Automated machine learning.

Project description

auto-sklearn

auto-sklearn is an automated machine learning toolkit and a drop-in replacement for a scikit-learn estimator.

Find the documentation here

Automated Machine Learning in four lines of code

import autosklearn.classification
cls = autosklearn.classification.AutoSklearnClassifier()
cls.fit(X_train, y_train)
predictions = cls.predict(X_test)

Relevant publications

Efficient and Robust Automated Machine Learning
Matthias Feurer, Aaron Klein, Katharina Eggensperger, Jost Springenberg, Manuel Blum and Frank Hutter
Advances in Neural Information Processing Systems 28 (2015)
http://papers.nips.cc/paper/5872-efficient-and-robust-automated-machine-learning.pdf

Auto-Sklearn 2.0: The Next Generation
Authors: Matthias Feurer, Katharina Eggensperger, Stefan Falkner, Marius Lindauer and Frank Hutter
arXiv:2007.04074 [cs.LG], 2020 https://arxiv.org/abs/2007.04074

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

auto-sklearn-0.12.3.tar.gz (6.1 MB view details)

Uploaded Source

File details

Details for the file auto-sklearn-0.12.3.tar.gz.

File metadata

  • Download URL: auto-sklearn-0.12.3.tar.gz
  • Upload date:
  • Size: 6.1 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/50.3.0 requests-toolbelt/0.9.1 tqdm/4.48.2 CPython/3.7.3

File hashes

Hashes for auto-sklearn-0.12.3.tar.gz
Algorithm Hash digest
SHA256 1222e39596b2d9cc129cfcaa2106467b5f11479f49e8b09fbf78750dd3dfcfab
MD5 ad9878be1703b342a0aefe4bced730ae
BLAKE2b-256 83384bffa24065793f5b4101db83b9b1d89199df9ba5c4651104e292702f2bef

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