13 skills found
yourh / AttentionXMLImplementation for "AttentionXML: Label Tree-based Attention-Aware Deep Model for High-Performance Extreme Multi-Label Text Classification"
OctoberChang / X TransformerX-Transformer: Taming Pretrained Transformers for eXtreme Multi-label Text Classification
kongds / LightXMLLightXML: Transformer with dynamic negative sampling for High-Performance Extreme Multi-label Text Classification
yuzhimanhua / MAPLEThe Effect of Metadata on Scientific Literature Tagging: A Cross-Field Cross-Model Study (WWW'23)
siddsax / XML CNNPytorch implementation of the paper Deep learning for extreme multi-label text classification
HX-idiot / Hybrid Attention XMLPytorch codes for "Label-aware Document Representation via Hybrid Attention for Extreme Multi-Label Text Classification"
ajayshewale / Sentiment Analysis Of Text Data Tweets This project addresses the problem of sentiment analysis on Twitter. The goal of this project was to predict sentiment for the given Twitter post using Python. Sentiment analysis can predict many different emotions attached to the text, but in this report, only 3 major were considered: positive, negative and neutral. The training dataset was small (just over 5900 examples) and the data within it was highly skewed, which greatly impacted on the difficulty of building a good classifier. After creating a lot of custom features, utilizing bag-of-words representations and applying the Extreme Gradient Boosting algorithm, the classification accuracy at the level of 58% was achieved. Analysing the public sentiment as firms trying to find out the response of their products in the market, predicting political elections and predicting socioeconomic phenomena like the stock exchange.
FrancesZhou / XMTCExtreme Multi-label Text Classification
YunseobShin / Tail With X BERTExtreme Multi-label Text Classification based on X-BERT with GCN and Clustering modules
yu54ku / Xml CnnImplementation of "Deep Learning for Extreme Multi-label Text Classification" using PyTorch.
angrysky56 / Astermind Elm MCPThis is an **on-device, extremely fast text classifier** using Extreme Learning Machines - perfect for: - Real-time sentiment analysis - Spam detection - Topic classification - Any text categorization task where millisecond training speed matters - Generating text embeddings for similarity comparisons
jimmy646 / XML CNNCode for sigir 2017 paper "Deep learning for extreme multi-label text classification"
7avenged / Classify AgeExtreme data preprocessing and model development for text classification using scikit learn, NLTK etc..
