UCLA Master of Quantitative Economics Project for ECON 412
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Updated
May 2, 2021 - HTML
UCLA Master of Quantitative Economics Project for ECON 412
Email Spam Classifier will help people identify Spam E-Mails similar to the Spam encountered earlier, which are stored in a vast library of Spam E-Mails. This product will also help in identifying new Potential Spam E-Mails from known & unknown sources.
This project includes implementation of supervised machine learning algorithms in R language.
This project detects spam messages in SMS, including those written in regional languages typed in English. It uses an extended SMS dataset and applies the Monte Carlo method with various supervised learning algorithms to improve spam detection.
Simple Naive Bayes Spam Classifier
In this study we seek to predict employee attrition with KNN clustering and Naive Bayes, and to predict employee salary using multiple linear regression
Help For All (Mozilla Open Lab 2020)
The Spam Detector for Email and SMS is a software tool that analyzes messages sent via email or SMS to identify and filter out spam. It uses machine learning algorithms to scan messages and determine whether they are spam or not, based on a variety of factors.
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