The code for the ACL 2023 paper "Linear Classifier: An Often-Forgotten Baseline for Text Classification".

Multi-Tags Predictor for SO Questions Built with Chrome Extension

Multi-Label Learning from Single Positive Labels - CVPR 2021

A python app to predict Att&ck tactics and techniques from cyber threat reports

A repository for training transformer based models

A multi-label classifier based on PLM-ICD paper

Tools for multi-label classification problems.

多标签文本分类，多标签分类，文本分类, multi-label, classifier, text classification, BERT, seq2seq，attention, multi-label-classification

This code is a part of my doctoral research at PPG-CC/DC/UFSCar in colaboration with Ku Leuven in Belgium.

Repository of the paper "Community Detection Methods for Multi-Label Classification" publish in BRACIS 2023

This code is part of my Ph.D. research. This code selects the best partition using the CLUS framework. We choose the partition with the best Micro-F1.

This code is part of my PhD research. This code select the best partition using the CLUS framework. We choose the partition with the best Macro-F1.

This code is part of my doctoral research. It's oracle experimentation of Bell Partitions using the CLUS framework.

This code is part of my PhD research. This code generate hybrid partitions using Kohonen to modeling the labels correlations, and HClust to partitioning the label space.

This code is part of my doctoral research. The aim is to generate a specific version of random partitions for multilabel classification.

This code is part of my doctoral research. The aim is to generate partitions from the Jaccard index for multilabel classification.

This code is part of my Ph.D. research. Test the best hybrid partition chosen with Micro-F1 criteria using Clus framework.

Compute Friedman and Nemenyi Statistical Tests for Multilabel Classification

This code is part of my doctoral research. The aim is to generate a specific version of random partitions for multilabel classification.

This code is part of my doctoral research. The aim is to generate a specific version of random partitions for multilabel classification.

This code is part of my Ph.D. research. The aim is generate label co-ocurrence graphs from similarity matrices

This code is part of my doctoral research. The aim is test the best hybrid partitions chosen with silhouette coefficient. But here we using a chain of hybrid partitions to do the test.

This code is part of my Ph.D. research. The aim is generate similarity matrices from similarity measures.

This code is part of my PhD research. This code select the best partition using the silhouete coefficient.

This repository hold all experiments conducted during my PhD (2019-2023). HPML means "Hybrid Partitions for Multi-Label Classification". SET-UP-1

An efficient implementation of Partitioned Label Trees & its variations for extreme multi-label classification

Extremely simple and fast extreme multi-class and multi-label classifiers.

An example implementation of the FabricNet paper.

Eye Disease Diagnosis

Contains our files for the 'Artificial Intelligence on Social Media' Track at FIRE 2023