python - Imbalance in scikit-learn

Question

I'm using scikit-learn in my Python program in order to perform some machine-learning operations. The problem is that my data-set has severe imbalance issues.

Is anyone familiar with a solution for imbalance in scikit-learn or in python in general? In Java there's the SMOTE mechanizm. Is there something parallel in python?

question from:https://stackoverflow.com/questions/15065833/imbalance-in-scikit-learn

Answer 1

There is a new one here

https://github.com/scikit-learn-contrib/imbalanced-learn

It contains many algorithms in the following categories, including SMOTE

• Under-sampling the majority class(es).
• Over-sampling the minority class.
• Combining over- and under-sampling.
• Create ensemble balanced sets.