https://github.com/blinksta1ker/spam-mail-classification
Supervised ML model using Logistic Regression model to classify an email as Ham or Spam
https://github.com/blinksta1ker/spam-mail-classification
jupyter-notebook logistic-regression machine-learning numpy pandas python sklearn supervised-machine-learning
Last synced: about 2 months ago
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Supervised ML model using Logistic Regression model to classify an email as Ham or Spam
- Host: GitHub
- URL: https://github.com/blinksta1ker/spam-mail-classification
- Owner: BLinKSta1Ker
- Created: 2024-11-26T11:56:44.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-11-26T12:01:39.000Z (over 1 year ago)
- Last Synced: 2025-01-26T15:28:50.107Z (over 1 year ago)
- Topics: jupyter-notebook, logistic-regression, machine-learning, numpy, pandas, python, sklearn, supervised-machine-learning
- Language: Jupyter Notebook
- Homepage:
- Size: 249 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-Mail-Classification
This project is a machine learning-based spam email detection system. It uses a logistic regression model to classify emails as either "spam" or "ham" (legitimate). The system is implemented in Python and leverages natural language processing (NLP) techniques to transform email text into feature vectors.
## Features
- Preprocesses email data to handle missing values.
- Encodes target labels for classification.
- Extracts features using **TF-IDF Vectorizer**.
- Trains a logistic regression model for classification.
- Evaluates the model's performance on training and test data.
- Allows for input-based email classification.
## Technologies Used
- Python
- Pandas for data manipulation
- Scikit-learn for machine learning and NLP
- TF-IDF Vectorizer for feature extraction