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The SMS Spam Collection is a public set of SMS labeled messages that have been collected for mobile phone spam research.

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adzict/sms_spam_classification

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SMS Spam Classification

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Table of Contents

  1. Project Introduction
  2. Technologies Used
  3. Methods Used
  4. Project Description
  5. Licences
  6. Contact

Project Introduction

The SMS Spam Collection is a public set of SMS labeled messages that have been collected for mobile phone spam research. The goal of this project is to develop a machine learning model that can accurately classify SMS messages as either "spam" or "ham". This is important because spam messages can be a nuisance and even pose a security risk if they contain phishing scams or malicious links. By accurately identifying spam messages, users can avoid them and better protect their personal information.

Technologies Used

Methods Used

  • Data Processing / Data Cleaning
  • Data Analysis
  • Data Visualization
  • Text Preprocessing
  • Predictive Modeling and Hyperparameter Tuning
  • Evaluating Model Results
  • Reporting

Project Description

This project is a machine learning model that classifies SMS messages as either "spam" or "ham" (non-spam). The model achieved an accuracy of 0.97 using Multilayer Perceptron.

Data Sources

The data was obtained here

File Descriptions

Licenses

Database Contents License (DbCL) v1.0

Contact

Find me on LinkedIn, Twitter or adzictanja.com.

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The SMS Spam Collection is a public set of SMS labeled messages that have been collected for mobile phone spam research.

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