# Spam Detection — Arabic (Naive Bayes)
A spam/ham text classifier for Arabic messages, built with a custom Arabic-aware
preprocessing pipeline (tatweel/tashkeel stripping, tokenization, stopword
removal) 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,
tatweel (تطويل) and tashkeel (تشكيل) stripping via `pyarabic`, tokenization,
Arabic stopword removal
- **Hyperparameters:** Tuned via GridSearchCV (alpha smoothing)
- **Accuracy:** 97.6% on held-out test set
## Intended Use
Binary spam classification for Arabic 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
(via `langdetect`).
## How to Use
\```python
import joblib
model = joblib.load("spam_ar_nb.joblib")
predict…
