{"repo":"AmirhosseinHonardoust/Fake-News-Detector","free":true,"listed":false,"github":"https://github.com/AmirhosseinHonardoust/Fake-News-Detector","clone":"git clone https://github.com/AmirhosseinHonardoust/Fake-News-Detector.git","description":"A professional TF-IDF + Logistic Regression style-risk classifier for educational fake-news detection, with a Streamlit dashboard, honest evaluation, uncertainty handling, and leakage analysis.","language":"Python","stars":148,"topics":["ai-project","data-science","data-visualization","fake-news-detection","kaggle-dataset","logistic-regression","machine-learning","misinformation","news-analysis","nlp"],"license":"MIT","category":"machine-learning","readme_excerpt":"Fake News Style-Risk Detector A responsible machine learning project that turns news text into a style-risk signal , using a TF-IDF + Logistic Regression pipeline with honest evaluation , dataset leakage analysis , leakage-controlled training , checksum-verified model loading , a Streamlit dashboard , and command-line inference . Important: This project is a style-risk detector and educational demo , not a real-world fact-checker. The model, thresholds, and reports are designed to demonstrate a professional, honest text-classification workflow. They estimate whether text looks stylistically similar to real or fake examples in the training data; they do not verify claims against external evidence and should not be used for fact-checking, moderation, or any high-stakes decision. --- Table of Contents - Project Overview - What This Project Does - What This Project Does Not Do - Key Features - System Workflow - Project Structure - Installation - Quick Start - Training and Evaluation - Leakage Controls and Honest Evaluation - Model Output - Model Artifacts and Loading Safety - Streamlit Dashboard - Evaluation Metrics - Visual Reports - Testing and CI - Code Quality - Limitations - Responsible Use - Future Improvements - Tech Stack - Author - License --- Project Overview Fake-news detection is often presented as if a text classifier can decide whether an article is true or false. In reality, a classifier cannot verify factual truth without external evidence. A model score is only u","default_branch":null,"files":null,"tree":[],"storefront":"/r/AmirhosseinHonardoust","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/AmirhosseinHonardoust/Fake-News-Detector/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}