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Orange3-AutoML

This leverages several AutoML providers in Orange3.

Within the Add-ons installer, click on "Add more..." and type in orange3-automl
Currently the dependencies require 7.4 GBs of free disk space.

Installation Screenshot

Here is an example workflow using the iris dataset.

Example Orange3 Workflow using iris and the H2O Learner

Selection of AutoML Providers

Currently Supported

Provider Version Notes
h2o 3.4.4 Works well.
autogluon 1.4.0 There a bug on xgboost 2.0.3 through 2.1.3, which doesn't work with scikit-learn 1.7.1 (autogluon requires scikit-learn between 1.4.0 and 1.8.0)
auto-sklearn2 1.0.0 Works well.

Unsupported

I have tried the following packages and deemed them unsuitable.

Provider Version Reason
mlbox 0.8.5 Last updated 2020, requires old numpy (won't compile)
smac 2.3.1 Requires installing swig before pip install, Orange interface doesn't have that interface
auto-sklearn 0.24.2 Last updated 2022, Won't compile on python 3.12
tpot2 0.1.9a0 Installs, but ran into issues with server hangs.
Google CloudAutoML x Cloud-based, requires accounts, sends data to Google

Unevaluated

I have not researched the following yet.

Provider Version Reason
ludwig
transmogrifai
evalml
MLJAR

Release files for orange3-automl 0.1.3

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for orange3-automl 0.1.3
File Size Uploaded
orange3_automl-0.1.3.tar.gz 64.7 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for orange3-automl 0.1.3
File Interpreter ABI Platform
orange3_automl-0.1.3-py3-none-any.whl Python 3 none any Details

Total release size: 138.1 kB

Release files / orange3_automl-0.1.3.tar.gz

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