Popular GitHub Repositories for Multilabel Classification

Annif is a multi-algorithm automated subject indexing tool for libraries, archives and museums.

A PyTorch-based toolkit for natural language processing

Multi-Label Image Classification of Chest X-Rays In Pytorch

[CVPR 2023] Official code repository for "How you feelin'? Learning Emotions and Mental States in Movie Scenes". https://arxiv.org/abs/2304.05634

This is a reimplementation of AG-CNN. ("Thorax Disease Classification with Attention Guided Convolutional Neural Network","Diagnose like a Radiologist: Attention Guided Convolutional Neural Network for Thorax Disease Classification")

Toxic Language Detection in Social Media for Brazilian Portuguese: New Dataset and Multilingual Analysis

? A model for early detection of multiple faults in induction motors based on the use of PCA and multilabel decision-trees

Word2Vec encodings based search engine for Stackoverflow questions

A scikit-learn implementation of BOOMER - An Algorithm for Learning Gradient Boosted Multi-label Classification Rules

This repo contains implementation of advanced ML techniques. Includes model ensembles, cost-sensitive learning and dealing with class imbalance.

The traditional machine learning models give a lot of pain when we do not have sufficient labeled data for the specific task or domain we care about to train a reliable model. Transfer learning allows us to deal with these scenarios by leveraging the already existing labeled data of some related task or domain. We try to store this knowledge gained in solving the source task in the source domain and apply it to our problem of interest. In this work, I have utilized Transfer Learning utilizing BertForSequenceClassification model. Also tried RobertaForSequenceClassification and XLNetForSequenceClassification models for Fine-Tuning the Model.

A pytorch implementation of mpvae.

My Masters' thesis along with all codes and datsets.

Finto AI suggests subjects for a given text. It's based on Annif, a tool for automated subject indexing.

my study record for deep learning application with natural language processing problems

Multi-label classification using LLMs, with additional enhancements using quantization and LoRA (Low-Rank Adaptation). Get better performance on GPU.

This study aims to investigate the effectiveness of three Transformers (BERT, RoBERTa, XLNet) in handling data sparsity and cold start problems in the recommender system. We present a Transformer-based hybrid recommender system that predicts missing ratings and ex- tracts semantic embeddings from user reviews to mitigate the issues.

Covid-19 chest x_rays images multi-class classification while classes are (COVID, Pneumonia, normal)

MultiCLIP: A framework for multimodal-multilabel-multistage classification utilizing advanced pretrained models like CLIP and BLIP. 一个多模态多标签多阶段分类框架，利用像CLIP和BLIP这样的先进预训练模型。