# Spam Detection — English (Naive Bayes)
A lightweight spam/ham text classifier for English messages, built with a
custom preprocessing pipeline (tokenization, stopword removal, lemmatization)
and TF-IDF features feeding into a Multinomial Naive Bayes classifier.
## Model Details
- **Architecture:** TF-IDF + Multinomial Naive Bayes (scikit-learn Pipeline)
- **Preprocessing:** Custom transformer — hashtag/punctuation removal,
tokenization (NLTK), stopword removal, lemmatization (WordNet)
- **Hyperparameters:** Tuned via GridSearchCV (alpha smoothing)
- **Accuracy:** 99.4% on held-out test set
## Intended Use
Binary spam classification for English text messages/emails. Part of a
multilingual spam detection system that automatically routes text to a
language-specific model (English or Arabic) based on detected language.
## How to Use
\```python
import joblib
model = joblib.load("spam_eng_nb.joblib")
prediction = model.predict(["Congratulations! You've won a free prize, click h…
