imbalanced-classification
There are 114 repositories under imbalanced-classification topic.
ZhiningLiu1998/awesome-imbalanced-learning
😎 Everything about class-imbalanced/long-tail learning: papers, codes, frameworks, and libraries | 有关类别不平衡/长尾学习的一切：论文、代码、框架与库
YyzHarry/imbalanced-regression
[ICML 2021, Long Talk] Delving into Deep Imbalanced Regression
YyzHarry/imbalanced-semi-self
[NeurIPS 2020] Semi-Supervision (Unlabeled Data) & Self-Supervision Improve Class-Imbalanced / Long-Tailed Learning
ZhiningLiu1998/imbalanced-ensemble
🛠️ Class-imbalanced Ensemble Learning Toolbox. | 类别不平衡/长尾机器学习库
solegalli/machine-learning-imbalanced-data
Code repository for the online course Machine Learning with Imbalanced Data
jiawei-ren/BalancedMetaSoftmax-Classification
[NeurIPS 2020] Balanced Meta-Softmax for Long-Tailed Visual Recognition
YyzHarry/multi-domain-imbalance
[ECCV 2022] Multi-Domain Long-Tailed Recognition, Imbalanced Domain Generalization, and Beyond
Albertsr/Class-Imbalance
Cost-Sensitive Learning / ReSampling / Weighting / Thresholding / BorderlineSMOTE / AdaCost / etc.
TACJu/Bi-Sampling
This is the official PyTorch implementation of the paper "Rethinking Re-Sampling in Imbalanced Semi-Supervised Learning" (Ju He, Adam Kortylewski, Shaokang Yang, Shuai Liu, Cheng Yang, Changhu Wang, Alan Yuille).
mahsa91/RA-GCN-MedIA2022
Implementation code of RA-GCN: Graph Convolutional Network for Disease Prediction Problems with Imbalanced Data accepted by Medical Image Analysis Journal (MedIA 2022)
avikumart/Road-Traffic-Severity-Classification-Project
This is a multiclass classification project to classify severity of road accidents into three categories. this project is based on real-world data and dataset is also highly imbalanced.
B-Xi/TCSVT_2022_DGSSC
DGSSC: A Deep Generative Spectral-Spatial Classifier for Imbalanced Hyperspectral Imagery, TCSVT, 2022
LirongWu/GraphMixup
Code for ECML-PKDD 2022 paper "GraphMixup: Improving Class-Imbalanced Node Classification by Reinforcement Mixup and Self-supervised Context Prediction"
miriamspsantos/open-source-imbalance-overlap
A collection of Open Source Contributions in Learning from Imbalanced and Overlapped Data
jyansir/Text2Tree
(EMNLP 2023 Findings) Text2Tree: Aligning Text Representation to the Label Tree Hierarchy for Imbalanced Medical Classification.
ihaeyong/Maximum-Margin-LDAM
Learning Imbalanced Datasets With Maximum Margin Losss
phiyodr/multilabel-oversampling
Many algorithms for imbalanced data support binary and multiclass classification only. This approach is made for mulit-label classification (aka multi-target classification). :sunflower:
HwaiTengTeoh/Flight-Delays-Prediction-Using-Machine-Learning-Approach
Flight delays prediction and analysis: Machine Learning Approach
AnonAuthorAI/duplebalance
DuBE: Duple-balanced Ensemble Learning from Skewed Data
clementw168/Imbalanced-Quickdraw
Winning a competition on imbalanced image classification.
jlbrosnahan/Predicting-Indoor-Location-with-WiFi-Signals
Highly multi-class machine learning classification problem in Python
theochem/B3clf
Predictors for Blood-Brain Barrier Permeability with resampling strategies based on B3DB database.
wildoctopus/cbloss
Pytorch implementation of Class Balanced Loss based on Effective number of Samples
ejw-data/ml-myopia
A variety of machine learning techniques used to identify nearsighted patients
peterlipan/MRC_VFC
The souce code of MICCAI'23 paper: Combat Long-tails in Medical Classification with Relation-aware Consistency and Virtual Features Compensation
jobregon1212/rulecosi
RuleCOSI is a machine learning package that combine and simplifies tree ensembles and generates a single rule-based classifier that is smaller and simpler.
amajji/Multi-class-classification
Deployment of a classification model on a webapp using FLASK for the backend and html/CSS/JS for frontend
anilans029/Forecasting-Backorders-In-Inventory
Backorders are unavoidable, but by anticipating which things will be backordered, planning can be streamlined at several levels, preventing unexpected strain on production, logistics, and transportation. ERP systems generate a lot of data (mainly structured) and also contain a lot of historical data; if this data can be properly utilized, a predictive model to forecast backorders and plan accordingly can be constructed. Based on past data from inventories, supply chain, and sales, classify the products as going into backorder or not.
M-Hashemzadeh/RCSMOTE
RCSMOTE: Range-Controlled Synthetic Minority Over-sampling Technique for handling the class imbalance problem
rajoy99/keshik
Oversample class imbalanced tabular data by Denoising Diffusion Probabilistic Model (DDPM)
rjjfox/disaster-response-classification
Multilabel classification to categorise messages received during a disaster
SmellyArmure/OC_DS_Project7
Implémentation d'un modèle de scoring (OpenClassrooms | Data Scientist | Projet 7)
himanshu1729ch/Detecting-Early-Alzheimer-Classification-Healthcare
A very interesting repo towards Alzheimer disease (Healthcare) contains 2 important Notebooks one with handling the imbalance data and other without significantly handling the imbalance.
KelvinLam05/product_classification
Build a fastText product classification model that can predict a normalized category name for a product, given an unstructured textual representation.
splch/qbs
An effective and flexible Quantile-Based Balanced Sampling algorithm for addressing class imbalance in datasets while preserving the underlying data distribution, improving model performance across various machine learning applications.
thinhuos0913/credit_card_fraud_detection
Implement machine learning models which are able to recognize fraudulent credit card transactions so that customers are not charged for items that they did not purchase.