dwavesystems/dwave-scikit-learn-plugin
A plugin to scikit-learn for quantum-classical hybrid solving
This tool helps data scientists and machine learning practitioners simplify complex datasets by identifying the most impactful features. It takes your raw data and, using a quantum-classical hybrid solver, outputs a refined dataset containing only the most relevant features for your machine learning models, leading to potentially more accurate and efficient results. This is ideal for those working with large datasets where feature selection is a performance bottleneck.
Available on PyPI.
Use this if you are a data scientist or machine learning engineer struggling with large datasets and want to improve model performance and training time by intelligently reducing the number of input features using advanced quantum-hybrid methods.
Not ideal if your datasets are small, you are not working with machine learning workflows, or you do not have access to D-Wave's Leap quantum cloud service.
Stars
16
Forks
15
Language
Python
License
Apache-2.0
Category
Last pushed
Jan 14, 2026
Commits (30d)
0
Dependencies
5
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