There are 0 repository under passive-aggressive-classifier topic.
TfidfVectorizer & PassiveAggressiveClassifier
An NLP model to detect fake news and accurately classify a piece of news as REAL or FAKE trained on dataset provided by Kaggle.
A Django webapp that detects fake news with Machine Learning.
Penerapan TF-IDF Vectorizer dan Passive Aggressive Classifier dalam pendeteksian berita palsu dengan Python.
A simple Python model that uses TFIDF Vectorizer and Passive Agressive Classifier to detect fake and irrelevant news
Detect Real or Fake News. To build a model to accurately classify a piece of news as REAL or FAKE. Using sklearn, build a TfidfVectorizer on the provided dataset. Then, initialize a PassiveAggressive Classifier and fit the model. In the end, the accuracy score and the confusion matrix tell us how well our model fares.
Detecting 'FAKE' news using machine learning.
This is a simple model which first vectorizes the training data using TF-IDF and then uses Passive Aggressive Classifier to train on the input data.
Fake News Detection using Machine Learning is a comprehensive project that utilizes machine learning and natural language processing techniques to identify and classify fake news articles. The project includes data analysis, model training, and a real-time web application for detecting fake news.
A project which examines the prevalence of fake news in light of communication breakthroughs made possible by the rise of social networking sites.
TARP Project
Detect FAKE news using sklearn
CheckThis is a Fake News Detection website developed by Jonathan Lee as part of the Final Year Project (FYP). The aim of this project is to create a simple web application to help ease the process of verifying the validity of a news article online
Fake News Detection using Scikit-learn
This advanced python project of detecting fake news deals with fake and real news. Using sklearn, we build a TfidfVectorizer on our dataset. Then, we initialize a PassiveAggressive Classifier and fit the model. In the end, the accuracy score and the confusion matrix tell us how well our model fares.
This is my Machine Learning model created with PassiveAggressiveClassifier to detect a news as Real or Fake depending on it's contents.
A simple end-to-end project on fake v/s real news detection/classification.
This is a flask application that detects and identifies the fake or real news.
This webapp helps to find the inaccurate information around the world through news
Implementation of some machine learning algorithms for classification on the iris flowers data set
Fake News Detection using Machine Learning Algorithms and deploying using Flask
Fake news detection in English and Vietnamese 📰❌
NLP program to detect passive aggressive statements
Fake news detection system built using TF-IDF vectorization and passive-aggressive classifier, implemented in Python 3.
Model Comparison for Fake News Classification
"DressMeUp" project utilizes fashion images and color combinations to achieve image classification for clothing combinations. Algorithms include SGD (SVM), Passive Aggressive Classifier, ResNet50 CNN, and EfficientNetV2-S CNN with K-Means for color analysis. Achieved accuracy exceeds 90%. Built with Python, Scikit-Learn, TensorFlow, and Streamlit.
Projet de NLTP comparant des approches supervisées et non supervisées dans le cadre de la formation d'ingénieur machine Learning dispensé par Openclassrooms
Text classification model trained on the song lyrics of two similar artists, with the corpus built from web scraping and HTML parsing
Machine Learning - Binary Classification
TfidfVectorizer is a technique used to transform text data into numerical feature vectors.
Fake News Classification using Naive Bayes, Passive-Aggressive (PA) Classifier and Artificia Neural Network (ANN)
Fake News Detection with Multinomial NB Classifier and Passive Aggressive Classifier
YouTube Spam
Analyzing Instagram Reach