README.md

metadata

license: mit

Commit Classification Model

This is a Logistic Regression model for multi-label classification of commit messages.

Files

• logistic_model.joblib: Trained Logistic Regression model.
• tfidf_vectorizer.joblib: TF-IDF vectorizer for text preprocessing.
• label_binarizer.joblib: MultiLabelBinarizer for encoding/decoding labels.

How to Use

To use this model, load the files and preprocess your data as follows:

from joblib import load

# Load the model and preprocessing artifacts
model = load("logistic_model.joblib")
tfidf_vectorizer = load("tfidf_vectorizer.joblib")
mlb = load("label_binarizer.joblib")

# Example usage
new_messages = ["Fix bug in login system"]
X_new_tfidf = tfidf_vectorizer.transform(new_messages)
predictions = model.predict(X_new_tfidf)
predicted_labels = mlb.inverse_transform(predictions)
print(predicted_labels)