imbalanced-algorithms
Imbalance solver
A collection of algorithms and implementations for handling imbalanced data in machine learning
Python-based implementations of algorithms for learning on imbalanced data.
235 stars
13 watching
100 forks
Language: Python
last commit: about 3 years ago
Linked from 1 awesome list
data-scienceimbalanced-datamachine-learningnotre-damepython
krzjoa/awesome-python-data-scienceRelated projects:
| Repository | Description | Stars |
|---|---|---|
 zhiningliu1998/imbalanced-ensemble | A library that enables quick and efficient ensemble learning on imbalanced datasets through various over-/under-sampling methods and algorithms | 340 |
 mmendiet/fedalign | A federated learning framework designed to mitigate data heterogeneity in distributed learning settings. | 55 |
 mingruiliu-ml-lab/episode | An algorithm for Federated Learning with heterogeneous data, designed to optimize deep neural networks and improve performance | 2 |
 hyhmia/distrans | Improves federated learning models by addressing data heterogeneity through distributional transformation | 5 |
 ljb121002/fednar | A Python implementation of federated optimization algorithm with normalized annealing regularization. | 6 |
 gdisag/gradient_disaggregation | An algorithm that breaks secure aggregation protocols in federated learning by recovering individual model updates from aggregated sums | 14 |
 gaoliang13/feddc | Federated learning algorithm that adapts to non-IID data by decoupling and correcting for local drift | 81 |
 iwang05/fluid | Federated learning algorithm to mitigate stragglers in distributed machine learning | 5 |
 xjtushujun/meta-weight-net | This is an implementation of a meta-learning algorithm to address class imbalance issues in deep learning models with noisy labels. | 284 |
 younghjung/onlinemlrboostingwithvfdt | An implementation of online multi-label ranking boosting using VFDT as weak learners | 4 |
 divyansh03/fedexp | An implementation of a federated averaging algorithm with an extrapolation approach to speed up distributed machine learning training on client-held data. | 9 |
 unc-optimization/feddr | An implementation of algorithms for nonconvex federated learning optimization | 8 |
 mop/bier | This project implements a deep metric learning framework using an adversarial auxiliary loss to improve robustness. | 39 |
 iamsaswata/imdlib | Downloads and processes binary IMD meteorological data in Python | 30 |
 sahith02/machine-learning-algorithms | A comprehensive resource for machine learning and deep learning algorithms | 295 |