automl / automl/auto-sklearn

Contributing more "building blocks"

Open
#116 4 comments 0 reactions 0 assignees View on GitHub
enhancement
Dominant language
Python
Stars
8.1k
Forks
1.3k
PR merge metrics
No merged PRs in 30d

Description

Hi AutoML team, I can chip in some code and add more algorithm "building blocks" to autosklearn. For example, I can add Factorization Machines for classification problems.

What is a good place to start with this? Any code-traditions that you would like me to follow?

Contributor guide

Open the contributing guide

Research direction

The issue does not name a file, entry point, test, or established contribution path. Start by reviewing the auto-sklearn algorithm-component structure and existing classification components, then identify the project’s contribution guidance and tests; done would mean a Factorization Machines component is integrated and covered by the relevant tests.

Written by the indexing model from the issue text.

Assessment

Tech stack
python, scikit-learn
Domain
machine-learning
Issue type
Feature
Difficulty
5/5
Estimated time
Over a week
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
20/100

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