Multi-Label Text Classification
According to Wikipedia "In machine learning, multi-label classification and the strongly related problem of multi-output classification are variants of the classification problem where multiple labels may be assigned to each instance. Multi-label classification is a generalization of multiclass classification, which is the single-label problem of categorizing instances into precisely one of more than two classes; in the multi-label problem there is no constraint on how many of the classes the instance can be assigned to."
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Greatest papers with code
RMDL: Random Multimodel Deep Learning for Classification
• kk7nc/RMDL
• 
This paper introduces Random Multimodel Deep Learning (RMDL): a new ensemble, deep learning approach for classification.
SOTA for Document Classification on WOS-11967
DOCUMENT CLASSIFICATION FACE RECOGNITION IMAGE CLASSIFICATION MULTI-LABEL TEXT CLASSIFICATION
Towards Scalable and Reliable Capsule Networks for Challenging NLP Applications
ACL 2019
• andyweizhao/capsule_text_classification
•
Obstacles hindering the development of capsule networks for challenging NLP applications include poor scalability to large output spaces and less reliable routing processes.
SOTA for Text Classification on RCV1 ([email protected] metric )
Investigating Capsule Networks with Dynamic Routing for Text Classification
EMNLP 2018
• andyweizhao/capsule_text_classification
•
In this study, we explore capsule networks with dynamic routing for text classification.
#4 best model for
Sentiment Analysis
on MR
MULTI-LABEL TEXT CLASSIFICATION SENTIMENT ANALYSIS SUBJECTIVITY ANALYSIS
PySS3: A Python package implementing a novel text classifier with visualization tools for Explainable AI
A recently introduced text classifier, called SS3, has obtained state-of-the-art performance on the CLEF's eRisk tasks.
DOCUMENT CLASSIFICATION MULTI-LABEL TEXT CLASSIFICATION SENTENCE CLASSIFICATION TEXT CATEGORIZATION
t-SS3: a text classifier with dynamic n-grams for early risk detection over text streams
SS3 was created to deal with ERD problems naturally since: it supports incremental training and classification over text streams, and it can visually explain its rationale.
SOTA for Depression Detection on eRisk 2017
ANOREXIA DETECTION DOCUMENT CLASSIFICATION MULTI-LABEL TEXT CLASSIFICATION SENTENCE CLASSIFICATION TEXT CATEGORIZATION
ML-Net: multi-label classification of biomedical texts with deep neural networks
Due to this nature, the multi-label text classification task is often considered to be more challenging compared to the binary or multi-class text classification problems.
FEATURE ENGINEERING MULTI-LABEL CLASSIFICATION MULTI-LABEL CLASSIFICATION OF BIOMEDICAL TEXTS MULTI-LABEL TEXT CLASSIFICATION
AttentionXML: Label Tree-based Attention-Aware Deep Model for High-Performance Extreme Multi-Label Text Classification
NeurIPS 2019
• yourh/AttentionXML
• 
We propose a new label tree-based deep learning model for XMTC, called AttentionXML, with two unique features: 1) a multi-label attention mechanism with raw text as input, which allows to capture the most relevant part of text to each label; and 2) a shallow and wide probabilistic label tree (PLT), which allows to handle millions of labels, especially for "tail labels".
MULTI-LABEL TEXT CLASSIFICATION NEWS ANNOTATION WEB PAGE TAGGING
AttentionXML: Label Tree-based Attention-Aware Deep Model for High-Performance Extreme Multi-Label Text Classification
NeurIPS 2019
• yourh/AttentionXML
•
We propose a new label tree-based deep learning model for XMTC, called AttentionXML, with two unique features: 1) a multi-label attention mechanism with raw text as input, which allows to capture the most relevant part of text to each label; and 2) a shallow and wide probabilistic label tree (PLT), which allows to handle millions of labels, especially for "tail labels".
MULTI-LABEL TEXT CLASSIFICATION NEWS ANNOTATION PRODUCT CATEGORIZATION WEB PAGE TAGGING
Comprehensive Evaluation of Deep Learning Architectures for Prediction of DNA/RNA Sequence Binding Specificities
For this purpose, we present deepRAM, an end-to-end deep learning tool that provides an implementation of novel and previously proposed architectures; its fully automatic model selection procedure allows us to perform a fair and unbiased comparison of deep learning architectures.
AUTOMATIC MACHINE LEARNING MODEL SELECTION MODEL SELECTION MULTI-LABEL TEXT CLASSIFICATION
Large-Scale Multi-Label Text Classification on EU Legislation
ACL 2019
• iliaschalkidis/lmtc-eurlex57k
•
We consider Large-Scale Multi-Label Text Classification (LMTC) in the legal domain.