imbalanced-ensemble

Ensemble learner

A library that enables quick and efficient ensemble learning on imbalanced datasets through various over-/under-sampling methods and algorithms

🛠️ Class-imbalanced Ensemble Learning Toolbox. | 类别不平衡/长尾机器学习库

GitHub

340 stars
9 watching
52 forks
Language: Python
last commit: 6 months ago
Linked from 1 awesome list

class-imbalanceclassificationdata-miningdata-scienceensembleensemble-imbalanced-learningensemble-learningensemble-modelimbalanced-classificationimbalanced-dataimbalanced-learninglong-tailmachine-learningmulti-class-classificationpythonpython3scikit-learnsklearn

Backlinks from these awesome lists:

Related projects:

Repository Description Stars
ikki407/stacking A Python library implementing Stacked Generalization (Ensemble Learning) for combining multiple machine learning models to improve prediction accuracy. 222
dialnd/imbalanced-algorithms A collection of algorithms and implementations for handling imbalanced data in machine learning 235
zackzikaixiao/fedgrab A tool for training federated learning models with adaptive gradient balancing to handle class imbalance in multi-client scenarios. 14
flennerhag/mlens A Python library for building and training ensemble machine learning models 849
mingruiliu-ml-lab/episode An algorithm for Federated Learning with heterogeneous data, designed to optimize deep neural networks and improve performance 2
xjtushujun/meta-weight-net A PyTorch implementation of a meta-learning algorithm for sample weighting in class-imbalanced datasets with noisy labels. 284
ron1818/phd_code A collection of source code and supporting materials for a PhD study on ensemble learning methods and machine learning algorithms. 45
reiinakano/xcessiv A tool to automate the creation and optimization of stacked machine learning ensembles. 1,268
benedekrozemberczki/shapley An open-source Python library for evaluating and explaining the contribution of individual classifiers in machine learning ensembles. 219
pengyang7881187/fedrl Enabling multiple agents to learn from heterogeneous environments without sharing their knowledge or data 56
zfancy/sfat Combating heterogeneity in federated learning by combining adversarial training with client-wise slack during aggregation 28
yamingguo98/fediir An implementation of a federated learning algorithm that generalizes to out-of-distribution scenarios using implicit invariant relationships 10
jianyizhang123/flop An experiment comparing different federated learning approaches for image classification tasks with non-iid datasets. 8
lyn1874/fedpvr An implementation of a federated learning algorithm for handling heterogeneous data 6
hyhmia/distrans Improves federated learning models by addressing data heterogeneity through distributional transformation 5