mageshcruz/spam-classifier-scikit

📧 Spam Classifier (Scikit-learn + spaCy)

This model classifies messages as spam or ham using traditional NLP techniques.

🧠 Model Details

• Preprocessing: Tokenization + Lemmatization using spaCy
• Vectorization: TF-IDF (1-2 grams)
• Feature Selection: Chi2 with top 1000 features
• Model: Logistic Regression (class_weight="balanced", max_iter=1000)
• Performance: ~87% accuracy on balanced test set (800 spam, 800 ham)

📦 Files

• spam_classifier_bundle.joblib: Includes trained model, TF-IDF vectorizer, label encoder, and feature selector

📥 Load Model (Example)

from huggingface_hub import hf_hub_download
import joblib

bundle = joblib.load(hf_hub_download("mageshcruz/spam-classifier-scikit", "spam_classifier.joblib"))
model = bundle["model"]
vector = bundle["vectorizer"]
selector = bundle["selector"]
le = bundle["label_encoder"]