Imbalanced-learn (imported as imblearn) is an open source, MIT-licensed library relying on scikit-learn (imported as sklearn) and provides tools when dealing with classification with imbalanced classes.

Features

  • API documentation
  • Examples available
  • Testing available
  • Documentation available
  • MIT-licensed library
  • Tools when dealing with classification with imbalanced classes

Project Samples

Project Activity

See All Activity >

Categories

Machine Learning

License

MIT License

Follow imbalanced-learn

imbalanced-learn Web Site

Other Useful Business Software
Build Securely on AWS with Proven Frameworks Icon
Build Securely on AWS with Proven Frameworks

Lay a foundation for success with Tested Reference Architectures developed by Fortinet’s experts. Learn more in this white paper.

Moving to the cloud brings new challenges. How can you manage a larger attack surface while ensuring great network performance? Turn to Fortinet’s Tested Reference Architectures, blueprints for designing and securing cloud environments built by cybersecurity experts. Learn more and explore use cases in this white paper.
Download Now
Rate This Project
Login To Rate This Project

User Reviews

Be the first to post a review of imbalanced-learn!

Additional Project Details

Operating Systems

Linux, Mac, Windows

Programming Language

Python

Related Categories

Python Machine Learning Software

Registered

2024-07-31