Spam Message Classifier (ML + Flask API)

Overview

This project is a machine learning-based spam message classifier that detects whether a given message is Spam or Not Spam using Natural Language Processing techniques.

Features

Text preprocessing (cleaning, stopword removal)
TF-IDF vectorization with n-grams
Model comparison (Logistic Regression vs Naive Bayes)
REST API using Flask
Modular project structure

Tech Stack

Python
Pandas, NumPy
Scikit-learn
NLTK
Flask

Model Details

Algorithm: Multinomial Naive Bayes
Accuracy: ~97%
Spam Recall: ~81%
Vectorization: TF-IDF (n-grams)

Project Structure

spam-classifier/
│
├── data/
├── model/
├── src/
│   ├── preprocess.py
│   ├── train.py
│   └── predict.py
│
├── app.py
├── requirements.txt
└── README.md

How to Run

1. Clone the repository

git clone <your-repo-link>
cd spam-classifier

2. Create virtual environment

python -m venv venv
venv\Scripts\activate

3. Install dependencies

pip install -r requirements.txt

4. Train the model

python src/train.py

5. Run the API

python app.py

6. Test API

Send POST request to:

http://127.0.0.1:5000/predict

Example:

{
  "message": "Win money now!!!"
}

Example Output

{
  "prediction": "Spam"
}