multi-label-learning

There are 4 repositories under multi-label-learning topic.

yourh / AttentionXML
Implementation for "AttentionXML: Label Tree-based Attention-Aware Deep Model for High-Performance Extreme Multi-Label Text Classification"
xml multi-label multi-label-classification multi-label-learning
Language:Python 237
ShimShim46 / HFT-CNN
Convolutional Neural Network based on Hierarchical Category Structure for Multi-label Short Text Categorization
machine-learning convolutional-neural-networks text-categorization multi-label-learning fine-tuning short-text
Language:Python 117
hellowangqian / multi-label-image-classification
A Baseline for Multi-Label Image Classification Using Ensemble Deep CNN
multi-label-learning multi-label-classification multi-label-image-classification
Language:Python 76
akshitac8 / BiAM
[ICCV 2021] Official Pytorch implementation for Discriminative Region-based Multi-Label Zero-Shot Learning SOTA results on NUS-WIDE and OpenImages
multi-label-zsl nus-wide openimages-v4 iccv2021 self-attention channel-attention generalized-zero-shot-learning zero-shot-learning multi-label-learning
Language:Python 60
rhgao / Deep-MIML-Network
Learning to Separate Object Sounds by Watching Unlabeled Video (ECCV 2018)
pytorch audio miml multi-instance-multi-label-learning multi-label-learning multi-instance
Language:Python 49
Correr-Zhou / SPML-AckTheUnknown
[ECCV 2022] Offical implementation of the paper "Acknowledging the Unknown for Multi-label Learning with Single Positive Labels".
computer-vision deep-learning eccv2022 machine-learning multi-label-image-classification multi-label-learning weakly-supervised-learning
Language:Python 37
monk1337 / Graph-Neural-networks-for-NLP
Graph Neural networks for NLP
nlp gnn gcn graph neural-network natural-language-processing machine-learning graph-neural-networks graph-networks graph-attention-networks attention-mechanism multi-label-classification multi-label-learning graph-nlp pytorch pytorch-geometric graph-natural-language-processing
23
wanglichenxj / Adaptive-Graph-Guided-Embedding-for-Multi-label-Annotation
AG2E: A novel adaptive graph based multi-label learning framework for multi-label annotation, image retrieval, and other applications.
multi-label-learning semi-supervised-learning adaptive-graphics image-retrieval
Language:MATLAB 20
verb_ambiguity
kiyoon / verb_ambiguity
Official implementation of "An Action Is Worth Multiple Words: Handling Ambiguity in Action Recognition", BMVC 2022
action-recognition activity-recognition label-noise multi-label-learning video video-understanding label-ambiguity multi-label-action-recognition-dataset single-positive-multi-label-learning
Language:Python 11
nirbhayjm / GenEML
Scalable Generative Models for Mullti-label Learning with Missing Labels
machine-learning bayesian-inference multi-label-learning online-learning
Language:Python 10
amjadseyedi / SPMLD
Self-Paced Multi-Label Learning with Diversity
self-paced-learning multi-label-learning manifold-optimization diversity
Language:MATLAB 9
PranjalSahu / DRML
Deep Region and Multi-label Learning for Facial Action Unit Detection
multi-label-learning drml deep-learning convolutional-neural-networks facial action-units
Language:Jupyter Notebook 9
kochlisGit / Advanced-ML
Advanced Machine Learning Algorithms including Cost-Sensitive Learning, Class Imbalances, Multi-Label Data, Multi-Instance Learning, Active Learning, Multi-Relational Data Mining, Interpretability in Python using Scikit-Learn.
advanced-ml machine-learning-algorithms machine-learning python numpy pandas cost-sensitive-learning class-imbalance multi-label-learning multi-instance-learning active-learning multi-relational-data-mining interpretability semi-supervised-learning sklearn scikit-learn tensorflow
Language:Jupyter Notebook 8
ChristianSch / skml
scikit-learn compatibel multi-label classification
machinelearning multi-label-classification scikit-learn machine-learning machine-learning-library multi-label-learning multi-label-problem python python3 artificial-intelligence data-science data-mining multi-label
Language:Python 6
Lxinyuelxy / multi-label-learn
multi-label-learning
Language:Python 6
hallamlab / mlLGPR
Metabolic pathway inference using multi-label classification with rich pathway features
pathway-prediction metagenomics multi-label-learning biocyc bioinformatics logistic-regression pathway-tools metacyc
Language:Python 5
rodolfomp123 / imb-mulan
The Mulan Framework with Multi-Label Resampling Algorithms
imbalanced-learning imbalanced-data multi-label-classification multilabel multi-label mulan-framework mulan imb-mulan imbalanceness-mulan imbalanceness multilabel-imbalance multi-label-imbalanceness multi-label-learning multi-label-imbalance imbalance-classification data-imbalance multi-label-problem
Language:HTML 5
saisrivatsan / tf-protoNN
Tensorflow ProtoNN for Multi-label learning (supports both single/multi-gpu usage)
tensorflow machine-learning multi-label-classification multi-label-learning extreme-machine-learning
Language:Python 5
zhaodwahu / LSGL
code of LSGL
machine-learning-algorithms multi-label-learning
Language:MATLAB 3
JiaWu-Repository / MSFS
[IEEE Transactions on Multimedia 2020] Multi-View Multi-Label Learning With Sparse Feature Selection for Image Annotation
multi-view-learning multi-label-learning feature-selection image-annotation
2
YuanchenBei / Awesome-Multi-Label-Learning-On-Graphs
A curated list of papers on multi-label learning on graphs (MLLG).
graph-neural-networks multi-label multi-label-classification multi-label-learning
2
KouYinan / LCIF
feature selection
correlation feature-selection multi-label-learning
Language:MATLAB 1
hallamlab / leADS
leADS: improved metabolic pathway inference based on active dataset subsampling
multi-label-imbalance multi-label-classfications multi-label-learning active-dataset-subsampling acquisition-functions metabolic-network biocyc metacyc metabolic-pathways metabolic-pathway-prediction metagenomics bioinformatics pathway-tools
Language:Python 0
illusionic / Multi_label-Image-Classification-Using-Automated-Approach
Multi-label Image Classification using Automated Approach.
image-classification multi-label-learning deep-neural-networks
Language:Python 0
JoshWarn / Multi-Label-Shapes-Toy-Dataset-Generator
An easy-to-use multi-label image dataset generator.
dataset-generation dataset-generator machine-learning machine-learning-datasets mit-license multi-class multi-label-classification multi-label-image-classification multi-label-learning
Language:Python 0
ml-lab-sau / Auxiliary-Label-Embedding-for-Multi-label-Learning-with-Missing-Labels
In this paper, we propose an approach for multi-label classification when label details are incomplete by learning auxiliary label matrix from the observed labels, and generating an embedding from learnt label correlations preserving the correlation structure in model coefficients.
multilabel multilabel-classification missing-labels multi-label multi-label-learning auxiliary-labels label-correlation-embedding
Language:MATLAB 0
ml-lab-sau / Discriminatory-Label-specific-Weights-for-Multi-label-Learning-with-Missing-Labels
To deal with the class imbalance problem in multi-label learning with missing labels, we propose Class Imbalance aware Missing labels Multi-label Learning, CIMML. Our proposed method handles class imbalance issue by constructing a label weight matrix with weight estimation guided by how frequently a label is present, absent, and unobserved.
class-imbalance missing-labels multi-label-learning label-correlation missing-label-aware-label-weights
Language:MATLAB 0
ml-lab-sau / Multi-label-learning-with-missing-labels-using-sparse-global-structure-for-label-specific-features
To deal with the issues emerging from incomplete labels and high-dimensional input space, we propose a multi-label learning approach based on identifying the label-specific features and constraining them with a sparse global structure. The sparse structural constraint helps maintain the typical characteristics of the multi-label learning data.
missing-labels multi-label-learning auxiliary-label-correlations label-specific-features sparse-global-structure
Language:MATLAB 0
arbasher / straSplit
Stratification of multi-label datasets
active-learning class-imbalance clustering community-detection graph-learning label-propagation multi-label-imbalance multi-label-learning partial-least-squares-regression stratification stratified-sampling
Language:HTML
h-ehsan / EMLNN
Ensemble-based Multi-Label Neural Network (EMLNN)
ensemble-learning multi-label-learning neural-networks multi-label-classification
Language:Python
hallamlab / reMap
reMap: relabeling metabolic pathway data with groups to improve prediction outcomes
relabel multi-label-classification metabolic-pathways multi-label-learning bags bags-of-pathways biocyc metacyc pathway2vec bioinformatics topic-modeling centroid embeddings groups groups-of-pathways
Language:Python
hallamlab / triUMPF
Metabolic pathway inference using non-negative matrix factorization with community detection
multi-label-classification multi-label-learning metabolic-pathways metabolic-reconstruction non-negative-matrix-factorization subnetwork community-detection pathway-prediction biocyc metagenomics bioinformatics metacyc pathway2ec-association-matrix
Language:Python
Sagnik07 / CraftML-An-Efficient-Clustering-based-Random-Forest-for-Extreme-Multi-label-Learning.
We explore extreme multi label learning using a random forest based algorithm. The parallelized implementation uses a K-Means clustering based partitioning approach to improve performance.
multi-label-learning cuda-programming random-forest kmeans-clustering
Language:Jupyter Notebook