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Multi-Label Text Classification

14 papers with code · Methodology
Subtask of 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

3 May 2018kk7nc/RMDL

This paper introduces Random Multimodel Deep Learning (RMDL): a new ensemble, deep learning approach for classification.

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.

MULTI-LABEL TEXT CLASSIFICATION QUESTION ANSWERING

t-SS3: a text classifier with dynamic n-grams for early risk detection over text streams

11 Nov 2019sergioburdisso/pyss3

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.

ANOREXIA DETECTION DOCUMENT CLASSIFICATION MULTI-LABEL TEXT CLASSIFICATION SENTENCE CLASSIFICATION TEXT CATEGORIZATION

ML-Net: multi-label classification of biomedical texts with deep neural networks

13 Nov 2018ncbi-nlp/BLUE_Benchmark

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

29 Jan 2019MedChaabane/deepRAM

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