https://github.com/fatimaafzaal/email_spam_classification

This code performs email spam classification using three machine learning models: Naive Bayes, Support Vector Machines (SVM), and Random Forest Classifier. It evaluates their performance using accuracy scores and classification reports, ultimately identifying Random Forest Classifier as the best performer among the three.
https://github.com/fatimaafzaal/email_spam_classification

ensemble-learning naive-bayes-classifier random-forest-classifier spam-email-classifier svm-classifier

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This code performs email spam classification using three machine learning models: Naive Bayes, Support Vector Machines (SVM), and Random Forest Classifier. It evaluates their performance using accuracy scores and classification reports, ultimately identifying Random Forest Classifier as the best performer among the three.

• Host: GitHub
• URL: https://github.com/fatimaafzaal/email_spam_classification
• Owner: fatimaAfzaal
• Created: 2024-06-01T14:17:49.000Z (6 months ago)
• Default Branch: main
• Last Pushed: 2024-06-02T06:11:12.000Z (6 months ago)
• Last Synced: 2024-06-02T16:30:25.965Z (6 months ago)
• Topics: ensemble-learning, naive-bayes-classifier, random-forest-classifier, spam-email-classifier, svm-classifier
• Language: Jupyter Notebook
• Homepage:
• Size: 18.6 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# email_spam_classification

This code performs email spam classification using three machine learning models: Naive Bayes, Support Vector Machines (SVM), and Random Forest Classifier. It evaluates their performance using accuracy scores and classification reports, ultimately identifying Random Forest Classifier as the best performer among the three.

### Dataset Link

https://drive.google.com/file/d/1_CiCJXnxAInttD67iEuuRiVx7FS-Zzv4/view