Fake News Detection with Model Selection and Hyperparameter Optimization in Python (>97% acc.)
Last Updated on July 18, 2023 by Editorial Team
Author(s): Giovanni Valdata
Originally published on Towards AI.
A practical guide on fake news detection with model selection and hyperparameter optimization
Photo by Nijwam Swargiary on Unsplash
This article aims at describing the model selection and hyperparameter tuning process to perform fake-news detection.
My previous article, in which I explained how the model selection is executed within the field of machine learning on an Amazon Kindle reviews dataset, has been a success among readers. The project presented a limit, though, given the size of the dataset containing roughly 1.000.000 reviews, we couldn’t deploy the algorithm on a good portion of unseen data. It was done on 50.000 records, approximately 5%, because of computing limitations.
In this article, the goal is to identify and tune… Read the full blog for free on Medium.
Join thousands of data leaders on the AI newsletter. Join over 80,000 subscribers and keep up to date with the latest developments in AI. From research to projects and ideas. If you are building an AI startup, an AI-related product, or a service, we invite you to consider becoming a sponsor.
Published via Towards AI