https://github.com/ishanmk/spam-email-classifier
https://github.com/ishanmk/spam-email-classifier
nlp regex spam spam-detection tfidf-vectorizer tokenization
Last synced: over 1 year ago
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- Host: GitHub
- URL: https://github.com/ishanmk/spam-email-classifier
- Owner: IshanMK
- Created: 2024-06-28T08:56:39.000Z (almost 2 years ago)
- Default Branch: main
- Last Pushed: 2024-06-28T11:52:33.000Z (almost 2 years ago)
- Last Synced: 2024-06-29T10:26:31.644Z (almost 2 years ago)
- Topics: nlp, regex, spam, spam-detection, tfidf-vectorizer, tokenization
- Language: Jupyter Notebook
- Homepage: https://spam-mail-classifier.streamlit.app
- Size: 414 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Spam Email Classifier using GradientBoostingClassifier
This repository is dedicated to a spam email classifier developed using GradientBoostingClassifier from scikit-learn. The classifier is trained on a labeled dataset of emails, utilizing NLP techniques for feature extraction and supervised learning for classification. Key features include:
- **GradientBoostingClassifier Implementation**: Implementation of GradientBoostingClassifier for training and predicting spam or legitimate (ham) emails.
- **Dataset Preparation**: Scripts for preprocessing the email dataset, including tokenization, TF-IDF vectorization, and feature engineering.
- **Model Evaluation**: Evaluation scripts to assess classifier performance using metrics such as accuracy, precision, recall, and F1-score.
- **Continuous Development**: Ongoing development to enhance model accuracy, optimize parameters, and explore additional features for improved classification.
- **Deployment Guide**: Documentation and scripts for deploying the model in production environments or integrating it into email services.
This project aims to provide a robust solution for detecting spam emails effectively, leveraging GradientBoostingClassifier for high-performance classification.