Improving News Classification Model Using Support Vector Machine and Naive Bayes

News classification merupakan aplikasi untuk melakukan prediksi kategori berita berdasarkan isi dari berita tersebut.

Framework for prompt-based Persian text classification using pre-trained language models, with K-shot learning, symbol tuning, and comprehensive evaluation metrics.

Development of the prediction model for the Pundits Review website used to predict the sentiment in football news articles - https://www.punditsreview.com/

Multi-label 24.kg Kyrgyz news articles classification into 20 topics: data & baselines

Interpseech 2024 - News Topic classification (dataset, evaluation and models source)

Sentiment analysis and topic modeling

Fake News Detection Engine using Natural Language Processing and Machine Learning

This repository contains Jupyter notebooks detailing the experiments conducted in our research paper on Ukrainian news classification. We introduce a framework for simple classification dataset creation with minimal labeling effort, and further compare several pretrained models for the Ukrainian language.

Text classification on AG News dataset using the state-of-the-art transformer model BERT.

A machine learning project that focuses on categorizing Chinese news articles.

Classify news on the basis of titles using Google's word2vec

News Classifier

Real & fake news prediction system using machine learning algorithms.

Machine Learning Development - News Classification NLP

The project involves developing a news classification system to distinguish between true and fake news using Logistic Regression and Decision Tree models. It includes data preprocessing, model training, and manual testing functionalities to evaluate the accuracy of the classifiers.

Experimenting with different classification algorithm and deep learning sequence processing technique to build a new classification model

News Category Classification using TF-IDF Vectorizer and Multinomial Naive Bayes with Hyperparameter Tuning