π§ Email Spam Detection Model
This repository hosts an optimized Machine Learning model designed to classify incoming emails into Spam (unwanted/fraudulent) or Ham (legitimate/safe). The model leverages classical Natural Language Processing (NLP) techniques coupled with a robust Scikit-Learn pipeline for efficient classification.
π Model Details
- Model Type: Text Classification (Binary Classification)
- Algorithm: Multinomial Naive Bayes / Logistic Regression (Scikit-Learn)
- Feature Extraction: TF-IDF (Term Frequency-Inverse Document Frequency) Vectorizer
- Language: English (en)
- License: MIT
π οΈ How to Use (Inference)
You can load and test this model locally on your machine using the Python code snippet provided below.
Requirements
Ensure you have the necessary dependencies installed:
pip install scikit-learn joblib pandas
Evaluation results
- Accuracy on Email Spam Datasetself-reported0.980