https://github.com/rootcode-creator/detection-of-spam-email-using-machine-learning
https://github.com/rootcode-creator/detection-of-spam-email-using-machine-learning
machine-learning matplotlib research scikit-learn spam-detection
Last synced: about 1 year ago
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- Host: GitHub
- URL: https://github.com/rootcode-creator/detection-of-spam-email-using-machine-learning
- Owner: rootcode-creator
- License: gpl-3.0
- Created: 2023-10-24T23:25:11.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2024-07-09T15:57:36.000Z (almost 2 years ago)
- Last Synced: 2025-02-07T11:16:58.871Z (over 1 year ago)
- Topics: machine-learning, matplotlib, research, scikit-learn, spam-detection
- Language: HTML
- Homepage:
- Size: 4.84 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Spam-email-detection-by-machine-learning
**This project detects safe and harmful emails based on email body characteristics. For doing the task, I have used machine learning classifier algorithms like Random Forest, Decision Tree, K-Neighbors, Logistic Regression, Gradient Boosting, Ada Boost, Multinomial Naive Bayes (MNB) etc. from the scikit-learn library. That made the detection of unsafe emails automatic. Hence, users will be free from the headache of the safety of their devices.**
This model used classifiers from the scikit-learn library to build the models and used a dataset from Kaggle even though I preprocessed the dataset and removed noise from the dataset.
**Dataset link: https://www.kaggle.com/datasets/subhajournal/phishingemails**