Orthogonal Model of Emotions

A Text Classifier created using Sci-Kit Learn

Author

C.J. Pitchford

Published

18 June 2025

Usage

# Load the model and vectorizer
def load_model_and_vectorizer(model_path='naive_bayes_model.pkl', vectorizer_path='vectorizer.pkl'):
    model = joblib.load(model_path)
    vectorizer = joblib.load(vectorizer_path)
    return model, vectorizer

# Function to predict the label of a new text
def predict_label(text, model, vectorizer):
    text_vec = vectorizer.transform([text])
    prediction = model.predict(text_vec)
    return prediction[0]

# Example usage
if __name__ == "__main__":
    model, vectorizer = load_model_and_vectorizer()
    new_text = "I really, really hope this works."
    predicted_label = predict_label(new_text, model, vectorizer)
    print(f'The predicted label for the text is: {predicted_label}')