IEEE

Evaluation of rule-based, CountVectorizer, and Word2Vec machine learning models for tweet analysis to improve disaster relief

Abstract: Social media platforms, such as Twitter, are being increasingly used by people as a means of requesting help during disaster events. Machine learning techniques can be used to identify ...
GitHub

cuML models not working with textattack library

Hi. I am new to using GPU. I am working on adversarial machine learning and earlier I have used the Textattack library for one of my projects using Sklearn and Keras models. For that I created the ...
Scientific Research Publishing

Analysis of Public Sentiment regarding COVID-19 Vaccines on the Social Media Platform Reddit ()

1 African Institute for Mathematical Sciences (AIMS)/AIMS-Cameroon, Limbe, Cameroon. 2 Department of Mathematics and Computer Science, Faculty of Science, University of Douala, Douala, Cameroon. 3 WMG ...
IEEE

A Machine Learning-Sentiment Analysis on Monkeypox Outbreak: An Extensive Dataset to Show the Polarity of Public Opinion From Twitter Tweets

Abstract: Research on sentiment analysis has proven to be very useful in public health, particularly in analyzing infectious diseases. As the world recovers from the onslaught of the COVID-19 pandemic ...
GitHub

CountVectorizer Performance Problem #5306

I was doing text classification task these days, and I found the CountVectorizer / TfidfVectorizer quite slow. Then I look into the source code, I found the the function CountVectorizer._count_vocab: ...