Alternatives and similar repositories for Tri-training

Users that are interested in Tri-training are comparing it to the libraries listed below

• Albertsr / Class-Imbalance
  Cost-Sensitive Learning / ReSampling / Weighting / Thresholding / BorderlineSMOTE / AdaCost / etc.
  ☆110Updated 5 years ago
• LitoNeo / pytorch-AutoEncoders
  Autoencoders in PyTorch
  ☆102Updated 6 years ago
• FuzhenZhuang / Transfer-Learning-Toolkit
  Transfer Learning Toolkit for Primary Researchers
  ☆106Updated 4 years ago
• upup123 / AAAI-2019-AFS
  The code of the AAAI-19 paper "AFS: An Attention-based mechanism for Supervised Feature Selection".
  ☆47Updated 6 years ago
• cainsmile / GA_for_Feature_Selection
  使用遗传算法结合决策树做特征选择/Using genetic algorithm for feature selection with decision tree
  ☆25Updated 7 years ago
• iamyuanchung / csdnn
  Theano implementation of Cost-Sensitive Deep Neural Networks
  ☆26Updated 7 years ago
• realWang-Wei / BroadLearningSystem
  here is the introduce of bls
  ☆73Updated 4 years ago
• fungtion / DSN
  Pytorch implementation of Domain Separation Networks
  ☆156Updated 6 years ago
• yangarbiter / multilabel-learn
  multilabel-learn: Multilabel-Classification Algorithms
  ☆36Updated 5 years ago
• ZhiningLiu1998 / self-paced-ensemble
  [ICDE'20] ⚖️ A general, efficient ensemble framework for imbalanced classification. | 泛用，高效，鲁棒的类别不平衡学习框架
  ☆262Updated last year
• iBelieveCJM / pseudo_label-pytorch
  The Simple and Efficient Semi-Supervised Learning Method for Deep Neural Networks
  ☆343Updated 7 years ago
• Daipuwei / DANN-MNIST
  这是论文Unsupervised Domain Adaptation by Backpropagation的复现代码，并完成了MNIST与MNIST-M数据集迁移，master和tf2分支代码为是基于tf2.x，tf1分支代码基于tf1.x
  ☆65Updated 4 years ago
• syorami / DDC-transfer-learning
  A simple implementation of Deep Domain Confusion: Maximizing for Domain Invariance
  ☆162Updated 7 years ago
• Deepayan137 / DeepClustering
  A pytorch implementation of the paper Unsupervised Deep Embedding for Clustering Analysis.
  ☆148Updated 6 years ago
• LiangjunFeng / Broad-Learning-System
  BLS Code
  ☆135Updated 7 years ago
• MonaSu9562 / HierarchicalTransferLearning
  Hierarchical Transfer Component Analysis and Hierarchical Joint Domian Adaption are implemented in this repository.
  ☆21Updated 7 years ago
• hinanmu / MLKNN
  The implementation of the paper 'Ml-knn: A Lazy Learning Approach to Multi-Label Learning' in Pattern Recognition 2006
  ☆43Updated 7 years ago
• CLaraRR / autoencoder_practice
  AutoEncoder implements by keras. Including AE, DAE, DAE_CNN, VAE, VAE_CNN, CVAE, Sparse AE, Stacked DAE.
  ☆41Updated 5 years ago
• yuntaodu / Transfer-learning-materials
  resource collection for transfer learning!
  ☆250Updated 2 years ago
• asahi417 / DeepDomainAdaptation
  Tensorflow deep learning based domain adaptation model implementations with experiment of estimate MNIST by SVHN data (SVHN -> MNIST): DA…
  ☆26Updated 6 years ago
• xuman-Amy / preprocessing
  数据预处理之缺失值处理，特征选择
  ☆22Updated 6 years ago
• ShayanPersonal / stacked-autoencoder-pytorch
  Stacked denoising convolutional autoencoder written in Pytorch for some experiments.
  ☆135Updated 2 years ago
• Silver-Shen / Stable_Linear_Model_Learning
  The implementation and addtional material of AAAI2020 paper "Stable Learning via Sample Reweighting"
  ☆18Updated 5 years ago
• zangzelin / Auto-encoder-AE-SAE-DAE-CAE-DAE-with-keras-in-Mnist-and-report
  ☆54Updated 6 years ago
• JaimeTang / PyTorch-and-TransferLearning
  基于PyTorch使用迁移学习完成项目
  ☆61Updated 7 years ago
• hanzhaoml / MDAN
  Demo code for the MDAN paper.
  ☆127Updated 5 years ago
• cyustcer / Deep-Feature-Selection
  Python (PyTorch) realization of Deep Feature Selection (Model, Algorithm)
  ☆17Updated 5 years ago
• BIT-DA / SSAN
  [ACMMM 2020] Code release for "Simultaneous Semantic Alignment Network for Heterogenous Domain Adaptation" https://arxiv.org/abs/2008.01…
  ☆31Updated 3 years ago
• Nana0606 / autoencoder
  个人练习，自编码器及其变形（理论+实践）
  ☆344Updated 6 years ago
• Isilendil / OSTL
  Online Semi-supervised Learning + Online Heterogeneous Transfer Learning
  ☆30Updated 10 years ago