Class Imbalance Solutions ML Frameworks

Tools and techniques for handling class imbalance in datasets, including resampling methods, algorithms, and evaluation frameworks. Does NOT include general data preprocessing, feature engineering, or domain-specific applications (e.g., fraud detection, disease detection).

There are 27 class imbalance solutions frameworks tracked. 1 score above 70 (verified tier). The highest-rated is scikit-learn-contrib/imbalanced-learn at 77/100 with 7,090 stars. 1 of the top 10 are actively maintained.

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#	Framework	Score	Tier	Stars	Language
1	scikit-learn-contrib/imbalanced-learn A Python Package to Tackle the Curse of Imbalanced Datasets in Machine Learning	77	Verified	7,090	Python
2	ZhiningLiu1998/imbalanced-ensemble 🛠️ Class-imbalanced Ensemble Learning Toolbox. \| 类别不平衡/长尾机器学习库 [NeurIPS'25]	64	Established	418	Python
3	solegalli/machine-learning-imbalanced-data Code repository for the online course Machine Learning with Imbalanced Data	51	Established	188	Jupyter Notebook
4	ZhiningLiu1998/awesome-imbalanced-learning 😎 Everything about class-imbalanced/long-tail learning: papers, codes,...	49	Emerging	1,516	—
5	getspams/spams-python Python interface for SPAMS (SPArse Modeling Software)	48	Emerging	21	C++
6	artefactory/mgs-grf MGS-GRF for imbalanced-mixed-tabular data (AISTATS 2026 and ECML-PKDD 2025)	46	Emerging	49	Python
7	dayyass/graph-based-clustering Graph-Based Clustering using connected components and spanning trees.	39	Emerging	28	Jupyter Notebook
8	ZhiningLiu1998/BAT [ICML'24] BAT: 🚀 Boost Class-imbalanced Node Classification with <10 lines...	37	Emerging	27	Python
9	SauravPattnaikCS60/Weighted-Class-Tfidf Weighted Class TFIDF technique to deal with imbalanced datasets	36	Emerging	14	Python
10	kaushalshetty/SMOTE Synthetic Minority Over-sampling Technique	34	Emerging	41	Python
11	getspams/spams-R R interface for SPAMS (SPArse Modeling Software)	33	Emerging	3	C++
12	JuliaAI/Imbalance.jl A Julia toolbox with resampling methods to correct for class imbalance.	33	Emerging	31	Julia
13	getspams/spams-devel SPAMS (SPArse Modeling Software)	33	Emerging	6	C++
14	SBNC-Bavlab/ML-Algorithms-Visualization-and-Positioning ML Algorithms Visualization and Positioning	31	Emerging	4	JavaScript
15	miriamspsantos/open-source-imbalance-overlap A collection of Open Source Contributions in Learning from Imbalanced and...	26	Experimental	20	—
16	splch/qbs An effective and flexible Quantile-Based Balanced Sampling algorithm for...	24	Experimental	3	Jupyter Notebook
17	jlenec/geom-imbalance 📊 Explore a geometric theory of class imbalance in machine learning and...	22	Experimental	—	Python
18	clementw168/Imbalanced-Quickdraw Winning a competition on imbalanced image classification.	20	Experimental	7	Jupyter Notebook
19	thecocolab/data-imbalance Evaluating the effect of data balance on different classification metrics	20	Experimental	8	Jupyter Notebook
20	antonio-leitao/dbsampler Python library for efficient sampling of the decision boundary of high...	20	Experimental	6	Rust
21	mr-september/Resample-Lab Resample Lab provides general guidelines on how to treat imbalanced datasets...	17	Experimental	—	TypeScript
22	obrunet/Spark_Computation_of_Connected_Component_in_Graphs Implementation of the "CCF: Fast and Scalable Connected Component...	14	Experimental	3	HTML
23	srash007/imbalanced-regression Research-oriented exploratory analysis of imbalanced regression problems,...	13	Experimental	—	Jupyter Notebook
24	AmiteshDTU/SSOMaj-SMOTE-SSOMin This is a hybrid intelligent sampling technique to tackle class-imbalance in...	11	Experimental	4	Java
25	dstarrago/mismote Class imbalance correction algorithm for multiple-instance data	11	Experimental	—	Java
26	dstarrago/MIClassImbalanceSolutions Sampling-based class imbalance solutions for multiple-instance classification	11	Experimental	—	Java
27	Blue16-WangFudi/KTS-UPLMC Reference implementation of the KTS-UPLMC classifier for imbalanced data.	11	Experimental	—	MATLAB

Comparisons in this category

imbalanced-learn and imbalanced-ensemble (77 vs 64) imbalanced-learn and machine-learning-imbalanced-data (77 vs 51) imbalanced-learn and data-imbalance (77 vs 20) imbalanced-ensemble and awesome-imbalanced-learning (64 vs 49) spams-python and spams-devel (48 vs 33) spams-python and spams-R (48 vs 33) spams-devel and spams-R (33 vs 33)