A Naive Bayes spam/ham classifier based on Bayes' Theorem. A bunch of emails is first used to train the classifier and then a previously unseen record is fed to predict the output.
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Updated
Jan 16, 2018 - Python
A Naive Bayes spam/ham classifier based on Bayes' Theorem. A bunch of emails is first used to train the classifier and then a previously unseen record is fed to predict the output.
Machine learning for filtering out spam in the ENRON spam dataset
A comprehensive comparision of kNN, Naive Bayes and Neural Network in Text Classification
A collection of Python scripts designed to streamline various tasks related to managing emails and PDF attachments. Easily extract clean email text, classify emails as automated or human-generated, process PDFs, and automatically fill PDF forms using saved user profile data.
This repo has email classifiers based on Naive Bayes classifier, Bernouilli Naive Bayes Classifier and Logistic Regression Classifier.
This is a Spam Email Classifier built using Python and Streamlit. It uses a pre-trained model to predict whether an email is Spam or Not Spam. The app also provides the probability scores for both categories, enhancing transparency and reliability of the prediction.
Developed a Naive Bayes classifier for classifying the E-mail is Spam or Ham message
Spam Email Detection using Naive Bayes
NaiveBayes classifier with an without stop words to classify Ham and Spam emails
This repository is made to support my application of MLH fellowship. This project had been done during my 2 years of work experience at Sailfin Technologies and is stored as a private repository before. The repository contains full process code from email cleaning, data modelling, database authentication (postgres for Salesforce), REST API build…
A Naive Bayes algorithm to classify spam emails
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