rankpruning
Noise cleaner
An algorithm and package for handling noisy labels in binary classification problems
🧹 Formerly for binary classification with noisy labels. Replaced by cleanlab.
82 stars
7 watching
14 forks
Language: Jupyter Notebook
last commit: almost 3 years ago
Linked from 1 awesome list
binary-classificationdenoisinglearning-with-confident-exampleslearning-with-errorsmachine-learningmachine-learning-algorithmsmislabelingnoise-ratesnoisy-learningrank-pruning-algorithmrankingsemi-supervised-learningtraining
subeeshvasu/awesome-learning-with-label-noiseRelated projects:
| Repository | Description | Stars |
|---|---|---|
| cgnorthcutt/cleanlab | A tool for evaluating and improving the fairness of machine learning models | 57 |
 blowin/blowincleancode | A C# code analyzer designed to simplify and clean up code by identifying common issues and bad practices. | 15 |
 pxiangwu/topofilter | Develops and evaluates machine learning algorithms to mitigate the effects of noisy labels in supervised learning. | 30 |
 nust-machine-intelligence-laboratory/jo-src | An implementation of a contrastive learning approach to address noisy labels in machine learning models | 5 |
 paulalbert31/labelnoisecorrection | An implementation of an unsupervised label noise modeling and loss correction approach for deep learning. | 221 |
 huanglabpurdue/ncs | An algorithm to reduce noise in images from sCMOS cameras | 29 |
 dirty-cat/dirty_cat | A Python library for handling and encoding dirty categorical data in machine learning | 17 |
 davified/clean-code-ml | Adapting clean code principles to machine learning and data science in Python | 714 |
 xiaoboxia/cdr | An implementation of a PyTorch-based deep learning method to improve robustness against noisy labels in image classification tasks | 75 |
 ucsc-real/cal | An implementation of a method to learn with instance-dependent label noise in deep learning models using PyTorch | 47 |
| ucsc-real/cores | An implementation of a method to learn from noisy labels in machine learning models with instance-dependent noise | 36 |
 xlearning-scu/2021-cvpr-mrl | Develops a robust learning framework to handle noisy labels in multimodal data and improve cross-modal retrieval. | 13 |
 matanatr96/decoderproburpsuite | A tool for cleaning and decoding HTTP response text to improve readability | 2 |
 moucheng2017/med-noisy-labels | Provides PyTorch implementation of a method to address noisy labels in medical image segmentation. | 71 |
 chenpf1025/idn | Provides tools and data for studying instance-dependent label noise in deep neural networks, with a focus on combating noisy labels | 35 |