JuliaAI/Imbalance.jl
A Julia toolbox with resampling methods to correct for class imbalance.
When building machine learning models, especially classification models, you often encounter situations where some categories of data are much rarer than others. This tool helps you prepare your datasets by adjusting the balance of these categories, ensuring your models don't overlook the important but scarce data points. It takes your existing dataset as input and outputs a new, rebalanced dataset that's ready for training more accurate classification models. This is for data scientists, machine learning engineers, and researchers working on classification tasks.
Use this if your classification model performs poorly on certain rare categories because your training data has an unequal number of examples for each category.
Not ideal if your dataset is already perfectly balanced across all classes, or if you are working on regression or unsupervised learning problems.
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Julia
License
MIT
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Last pushed
Dec 19, 2025
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