📂 SMS Spam Detection

This project classifies SMS messages as spam or ham (not spam). It compares multiple classifiers and vectorizers to determine the best performance.

Features

Classifiers:

• DecisionTreeClassifier

• CalibratedClassifierCV

• DummyClassifier

• PassiveAggressiveClassifier

• RidgeClassifier

Vectorizers:

• CountVectorizer

• TfidfVectorizer

• HashingVectorizer

FastApi

• fastapi is a python pacakge for building scalable backend apis
• for more info about fastapi you can my github repo on fastapi implementations

Dataset:

• A CSV file containing SMS messages labeled as either "spam" or "ham".

Usage

• clone this repo with git clone https://github.com/Adagedo/sms-spam-detector-sklearn.git
• install dependencies with pip install requirement.txt
• After running the model, you should see an output like this.
• To run the application, uvicorn main:app --reload
• what you will see INFO: Uvicorn running on http://localhost:8000 (Press CTRL+C to quit) \n INFO:Started reloader process [8976] using WatchFiles
• api test
• api test
• api test
• api test

📝 Notes

The CSV file should have at least two columns:

• v1: label (ham/spam)

• v2: message text

Results are printed to the console or just take a look at the csv file.